Data Scientist jobs at TreeHouse Foods

A leading global Bank is strengthening its Data Engineering & Production Support function, seeking an Azure Cloud Data Engineer to support mission-critical data pipelines, orchestrations, and ETL workloads within Azure. This is a hands-on, high-impact role focused on reliability, uptime, and seamless data movement across the enterprise. About the Role: You'll be the key specialist supporting Azure Data Factory and Databricks during a major cloud migration initiative. If you thrive in fast-paced production environments-solving pipeline failures, optimizing Spark jobs, and keeping complex data workflows running-this role gives you real responsibility, visibility, and technical ownership. Responsibilities: Support and troubleshoot Azure Data Factory pipelines and Databricks jobs across production environments. Ensure stability, performance, and uptime of ETL/ELT workflows during cloud migration initiatives. Perform root-cause analysis on pipeline failures, Spark issues, cluster timeouts, and data mismatches. Collaborate with engineering and DevOps teams to optimize workflows, deployments, and cloud integrations. Qualifications Strong experience with Azure Data Factory, Databricks, and Azure-based data engineering. Proven background in ETL/ELT processes, data integration, and orchestration. Solid understanding of cloud data services (ADLS Gen2, Azure SQL, Databricks, Functions, etc.). Hands-on experience in monitoring, debugging, and optimizing production data pipelines. Required Skills Azure Data Factory Databricks ETL/ELT processes Data integration Cloud data services Preferred Skills Experience with Azure SQL Knowledge of ADLS Gen2 Familiarity with Azure Functions

We are seeking an experienced Senior Big Data & Cloud Engineer to design, build, and deliver advanced API and data solutions that support financial goal planning, investment insights, and projection tools. This role is ideal for a seasoned engineer with 10+ years of hands-on experience in big data processing, distributed systems, cloud-native development, and end-to-end data pipeline engineering. You will work across retail, clearing, and custody platforms, leveraging modern cloud and big data technologies to solve complex engineering challenges. The role involves driving technology strategy, optimizing large-scale data systems, and collaborating across multiple engineering teams. Key Responsibilities Design and develop large-scale data movement services using Apache Spark (EMR) or Spring Batch. Build and maintain ETL workflows, distributed pipelines, and automated batch processes. Develop high-quality applications using Java, Scala, REST, and SOAP integrations. Implement cloud-native solutions leveraging AWS S3, EMR, EC2, Lambda, Step Functions, and related services. Work with modern storage formats and NoSQL databases to support high-volume workloads. Contribute to architectural discussions and code reviews across engineering teams. Drive innovation by identifying and implementing modern data engineering techniques. Maintain strong development practices across the full SDLC. Design and support multi-region disaster recovery (DR) strategies. Monitor, troubleshoot, and optimize distributed systems using advanced observability tools. Required Skills : 10+ years of experience in software/data engineering with strong big data expertise. Proven ability to design and optimize distributed systems handling large datasets. Strong communicator who collaborates effectively across teams. Ability to drive architectural improvements and influence engineering practices. Customer-focused mindset with commitment to delivering high-quality solutions. Adaptable, innovative, and passionate about modern data engineering trends.

Objective of the Job: This position focuses on problem solving by implementing actionable data-driven business solutions, predict emerging trends, providing recommendations to stakeholders by analyzing and modelling a vast variety of data. Duties and Responsibilities: 1) Upholds a high integrity for BRS Systems while supporting Safety, Environmental & Quality Systems 2) Identify business use cases in consultation business stake holders, peers and superiors. 3) Analyze data requirements, create models and provide solutions (combination of ML and Analytics) 4) Document the processes and mentor others in the team. 5) Participate in setting up an analytics platform for Self Service Analytics. Qualifications: 1) Bachelor's degree in computer science or engineering or related field; master's degree preferred. 2) Must have minimum 2 years of experience in Analytics and use of Machine Learning Algorithms. 3) Demonstrated ability in Visualization tools, ML Frameworks, and other related topics. 4) Entrepreneurial drive, with demonstrated ability to deliver projects on time 5) Strong aptitude for learning new technologies and analytics techniques Working Conditions and Physical Requirements: This position requires the ability to work on site or remote from the states of Arkansas, Tennessee, Texas , or Mississippi with occasional on-site visit as needed. Supervisory Responsibility: This position does not supervise others - the scope of the role may change as time progresses and organization grows.

Job Description Our client operates at the crossroads of energy and home services, fueled by the vision of a smarter, cleaner future. Committed to developing groundbreaking solutions, they aim to streamline their customers' lives by providing energy, protection, and smart services for their homes and businesses. Our client is seeking a Staff Data Scientist to design and deploy predictive models that enable intelligent home energy decisions: from forecasting comfort and cost to optimizing EV charging and demand response events. Develop Predictive Models: Build and deploy advanced models for occupancy, runtime, cost forecasting, anomaly detection, and preconditioning to enable comfort-aware, energy-efficient control and maintenance. Optimize Energy Operations: Use data-driven insights to improve the reliability and precision of Demand Response (DR), Time-of-Use (TOU) shifting, and Virtual Power Plant (VPP) strategies. Advance Data Quality & Scalability: Partner with data engineering to transform legacy data structures into robust, documented, and reusable data products that support ML and real-time analytics. Cross-Functional Collaboration: Work closely with product, engineering, and analytics teams to embed intelligence into production systems and shape future data-driven energy experiences. Communicate Impact: Translate complex model outcomes into actionable insights for both technical and non-technical audiences. Required Qualifications Proven expertise in predictive modeling, forecasting, and applied ML (e.g., regression, gradient boosting, time-series, causal inference). Experience working with large-scale event and sensor data, preferably within energy, IoT, or device-driven ecosystems. Strong proficiency in Python (Pandas, NumPy, scikit-learn, PySpark) and experience with distributed compute environments (Spark, Databricks, GCP). Ability to take models from concept to production in collaboration with engineering partners. Skilled in statistical analysis, feature engineering, and experimental design (e.g., A/B testing). Excellent communication and storytelling skills for complex, data-driven topics. Preferred Qualifications Experience with energy forecasting, thermal modeling, or Demand Response optimization. Understanding energy markets, Distributed Energy Resources (DER), and Virtual Power Plant (VPP) concepts. Familiarity with LLM or generative AI applications in analytics and optimization. Advanced degree (MS/PhD) in a quantitative field such as Statistics, Computer Science, or Engineering. 5+ years of industry experience, including demonstrated technical leadership on high-impact modeling initiatives.

Employee Type: Full time Job Type: Information Technology Data Management Job Posting Title: Supply Chain Data Scientist About Us: TreeHouse Foods (NYSE: THS) is a leading manufacturer of private label packaged foods and beverages, operating a network of over 20 production facilities and several corporate offices across the United States and Canada. At TreeHouse Foods, our commitment to excellence extends beyond our products and revolves around our people. We are investing in talent and creating a performance-based culture where employees can do their best work and develop their careers, directly impacting our mission to make high quality, affordable food for our customers, communities, and families. We hope you will consider joining the team and being part of our future. Named one of America's Best Large Employers by Forbes Magazine, we are proud to live by a strong set of values and strive to "Engage and Delight - One Customer at a Time." Guided by our values-Own It, Commit to Excellence, Be Agile, Speak Up, and Better Together. We are a diverse team driven by integrity, accountability, and a commitment to exceptional results. We embrace change, prioritize continuous learning, and foster collaboration, transparency, and healthy debate. Together, we set each other up for success to achieve enterprise-wide goals. What You Gain: * Competitive compensation and benefits program with no waiting period - you're eligible from your first day! * 401(k) program with 5% employer match and 100% vesting as soon as you enroll. * Comprehensive paid time off opportunities, including immediate access to four weeks of vacation, five sick days, parental leave and 11 company holidays (including two floating holidays). * Leaders who are invested in supporting your accelerated career growth, plus paid training, tuition reimbursement and a robust educational platform - DevelopU - with more than 10,000 free courses to support you along the way. * An inclusive working environment where you can build meaningful work relationships with a diverse group of professionals. Take advantage of opportunities to build on our team-oriented culture, such as joining one of our Employee Resource Groups. * Access to our wellness and employee assistance programs. Job Description: About the Role: Treehouse Foods' Integrated Planning team is looking for a talented and data-driven Supply Chain Data Scientist to enhance our supply chain forecasting capabilities in our Oak Brook, IL corporate office. This role is ideal for a professional who thrives on analytical challenges and is committed to making a tangible impact. We value collaborative problem-solvers who bring a strong analytical mindset and demonstrate curiosity, resilience, and commitment to continuous learning. If you are adaptable, results-oriented, and motivated by cross-functional teamwork, we encourage you to join our team in supporting Treehouse Foods' mission of delivering quality food products with efficiency and precision. You'll add value to this role by performing various functions including, but not limited to: * Analyze large, complex datasets to extract actionable insights, identify trends, and address supply chain challenges. * Develop, deploy, and maintain statistical demand planning and inventory optimization models using Blue Yonder or similar platforms across various business units. * Present complex data insights in a clear and effective manner to both technical and non-technical stakeholders. * Research and implement new data science techniques and technologies to enhance forecasting accuracy and supply chain performance. * Ensure analytical insights are seamlessly integrated into business processes and guide model deployment requirements, including adherence to QA standards. * Work with both technical and business stakeholders to identify technology-driven opportunities that deliver measurable business value. * Other duties as assigned. Important Details: * This is a hybrid role on first shift in Oak Brook, IL. * The anticipated compensation for this position ranges from $ 100,800 to $151,200 annually. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue-based metrics and business or organizational needs. For certain roles, the successful candidate may be eligible for annual discretionary merit compensation award, bonus and equity pay. You'll fit right in if you have: * Bachelor's or advanced degree in Statistics, Data Analytics, Applied Mathematics, or a related quantitative field; advanced degree preferred. * 5 or more years of experience in data science or machine learning roles, preferably within private-label CPG organizations. * Expertise in SQL and relational databases, proficiency with Blue Yonder or similar Supply Chain platform for statistical demand planning and inventory optimization. * Experience with machine learning libraries and frameworks (PyTorch, TensorFlow, NumPy) and data visualization tools (Tableau, PowerBI). * Strong quantitative, statistical, and data mining knowledge, including experience with techniques like regression, random forests, hierarchical clustering, deep learning, CNNs, and RNNs. * A strong desire to explore data-driven methodologies, with a focus on innovation and continuous improvement. Your TreeHouse Foods Career is Just a Click Away! Click on the "Apply" button or go directly to ****************************** to let us know you're ready to join our team! At TreeHouse Foods, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work to help us "Engage and Delight - One Customer at a Time". TreeHouse Foods is an Equal Opportunity Employer that prohibits discrimination or harassment of any type. All qualified applicants are considered for employment without regard to race, color, national origin, age, sex, sexual orientation, gender, gender identity or expression, disability status, protected veteran status, or any other characteristic protected by law. Applicants who require an accommodation to participate in the job application or hiring process should contact disability-accommodations@treehousefoods.com TreeHouse Use Only: #IND1

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings. Responsibilities: Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development. Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry's business objectives. Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models. Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment. Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications. Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team's technical capabilities. Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment. Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development. Qualifications: A bachelor's degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs). Experience with multimodal data processing (e.g., combining text, image, and 3D data). Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. Strong background in probability, statistics, and optimization techniques relevant to generative modeling. Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker). Familiar with software engineering principles, including version control, reproducibility, and continuous integration. Experience in the manufacturing, supply chain, or similar industries is a plus. #LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Job Description Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings. Responsibilities: Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development. Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry's business objectives. Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models. Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment. Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications. Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team's technical capabilities. Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment. Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development. Qualifications: A bachelor's degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs). Experience with multimodal data processing (e.g., combining text, image, and 3D data). Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. Strong background in probability, statistics, and optimization techniques relevant to generative modeling. Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker). Familiar with software engineering principles, including version control, reproducibility, and continuous integration. Experience in the manufacturing, supply chain, or similar industries is a plus. #LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Who is USP? The U.S. Pharmacopeial Convention (USP) is an independent scientific organization that collaborates with the world's leading health and science experts to develop rigorous quality standards for medicines, dietary supplements, and food ingredients. At USP, we believe that scientific excellence is driven by a commitment to fairness, integrity, and global collaboration. This belief is embedded in our core value of Passion for Quality and is demonstrated through the contributions of more than 1,300 professionals across twenty global locations, working to strengthen the supply of safe, high-quality medicines worldwide. At USP, we value inclusive scientific collaboration and recognize that attracting diverse expertise strengthens our ability to develop trusted public health standards. We foster an organizational culture that supports equitable access to mentorship, professional development, and leadership opportunities. Our partnerships, standards, and research reflect our belief that ensuring broad participation in scientific leadership results in stronger, more impactful outcomes for global health. USP is proud to be an equal employment opportunity employer (EEOE) and is committed to ensuring fair, merit-based selection processes that enable the best scientific minds-regardless of background-to contribute to advancing public health solutions worldwide. We provide reasonable accommodations to individuals with disabilities and uphold policies that create an inclusive and collaborative work environment. Brief Job Overview The USP Advanced Manufacturing Technologies (AMT) team seeks to continuously improve medicines through practical applications and solutions in advanced manufacturing and analytical technologies that increase medicine quality and strengthen supply chain resiliency. The AMT team helps make drugs in new ways, test the quality of drugs in new ways, and build more efficient, sustainable, and competitive industries both in the US and around the globe. To do this work, the AMT team brings together expertise in chemistry, biologics, engineering, data science, economics, business, and regulatory science. The AMT Data Scientist is a scientific professional who leverages data science expertise to support scientific, supply chain, and sustainability programs. This will include, but are not limited to, the following program areas: 1) MedSuRe Climate-smart work package building baseline and improvement models of manufacturing, energy, water, waste, and resource utilization; 2) AI/ML models to streamline pharmaceutical supply chain vulnerability and solution analyses; and 3) processing and modeling spectroscopy data generated by process analytical technologies (PAT) research and development solutions. The role emphasizes cross-disciplinary collaboration on time-sensitive externally and internally funded projects and development of proposals for new projects. The workload balance in these areas depends on external funding priorities and projects. This is a two-year fixed term position . The term may be extended based on external funding priorities and projects. How will YOU create impact here at USP? As part of our mission to advance scientific rigor and public health standards, you will play a vital role in increasing global access to high-quality medicines through public standards and related programs. USP prioritizes scientific integrity, regulatory excellence, and evidence-based decision-making to ensure health systems worldwide can rely on strong, tested, and globally relevant quality standards. Additionally, USP's People and Culture division, in partnership with the Equity Office, invests in leadership and workforce development to equip all employees with the skills to create high-performing, inclusive teams. This includes training in equitable management practices and tools to promote engaged, collaborative, and results-driven work environments. The AMT Data Scientist has the following responsibilities: Create, validate, and continually refine multivariate models using principal component analysis (PCA), partial least squares (PLS), and advanced machine learning (ML) algorithms. Use of normalization, mean-centering, and cross-validation strategies to ensure model robustness and interpretability while managing high-dimensional data sets. Employ advanced model-based approaches for scenario simulation, risk prediction, and mitigation optioning. Apply data science expertise to the development of carbon footprint models of pharmaceutical manufacturing that incorporate energy, process technologies, water, waste, transportation, and packaging. Build, validate, and implement life-cycle assessment models and tools for current and future applications. Build, validate, and implement predictive models in both the sustainable manufacturing and supply chain spaces. Model trade-offs and conduct scenario analysis to optimize yield, reduce waste, and cost of production. Develop AL/ML tools for internal use within the AMT team to improve efficiency and quality of complex, technical and economic analyses. Use of AI/ML-driven retrosynthetic tools (e.g., AIZynthFinder, SYNCHEM) and multi-target convergent synthesis frameworks to design efficient, cost-effective pathways for active pharmaceutical ingredients (APIs) and intermediates. In collaboration with USP science staff, analyze high-dimensional data from analytical platforms such as NIR, Raman, FTIR, and HPLC employing chemometric methods to extract actionable insights. Author and execute protocols for method design, model building, and validation for advanced manufacturing technologies. Act as a subject-matter expert on data science on cross-functional projects, including the technical design of proposals Ensure all work is done on-time, meets client expectations, and exemplifies the trust, quality, and reliability expected from a USP solution. Other duties as assigned. Who is USP Looking For? The successful candidate will have a demonstrated understanding of our mission, commitment to excellence through inclusive and equitable behaviors and practices, ability to quickly build credibility with stakeholders, along with the following competencies and experience: Bachelor's Degree and seven (7) years of relevant experience; master's degree and five (5) years of relevant experience; or a Ph.D. and (3) years of relevant experience required. Demonstrated experience applying statistical techniques to complex systems as well as developing or applying techniques such as pre-processing, classification, regression, clustering, dimensionality reduction and model selection. Programming and computational abilities in data science languages and frameworks (e.g., Python-Pandas, scikit-learn, TensorFlow; R; MATLAB; Pyomo). Strong analytical reasoning, critical thinking, and troubleshooting ability. High attention to detail and integrity. Demonstrates initiative to solve problems and develop solutions on a deadline. Solid communications skills - both written and oral. Desire to affect change and drive public health impact. Additional Desired Preferences Preferred degrees in data science, statistics, chemical engineering, or closely related field with significant emphasis in mathematical and statistical methods to extract meaningful information. Working knowledge of manufacturing in the pharmaceutical industry. Familiarity with the applying data science to climate risk or other environmental domains. Experience executing on contract work. Supervisory Responsibilities None, this is an individual contributor role. Benefits USP provides the benefits to protect yourself and your family today and tomorrow. From company-paid time off and comprehensive healthcare options to retirement savings, you can have peace of mind that your personal and financial well-being is protected. Compensation Base Salary Range: USD $87,200.00 - $113,450.00 annually. Target Annual Bonus: % Varies based on level of role. Individual compensation packages are based on various factors unique to each candidate's skill set, experience, qualifications, equity, and other job-related reasons. Note: USP does not accept unsolicited resumes from 3rd party recruitment agencies and is not responsible for fees from recruiters or other agencies except under specific written agreement with USP.

We believe that the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid's network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Data team within Plaid's Fraud organization builds the machine learning systems that power Plaid's newest fraud detection products, leveraging the breadth of Plaid's network data to stop fraud before it occurs. We manage the full lifecycle of these systems-from feature pipeline development and model training to deployment, serving, and monitoring-ensuring our solutions scale reliably as we grow to support hundreds of customers. As a Data Scientist on Plaid's Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You'll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners. You will run backtests on customer traffic to evaluate model and rule performance, uncover high-value opportunities, and generate insights that support sales motions and customer expansion. You'll also design the underlying data models and schemas that enable efficient, reliable analysis and reporting. In close partnership with Product and Engineering, you will help design and evaluate experiments that shape new customer-facing features and inform the future of our fraud products. ***We are open to remote candidates***Responsibilities Work at the intersection of product analytics, machine learning, and fraud/risk to drive meaningful product improvements. Own the metrics, dashboards, and experimentation frameworks that inform product strategy and decision-making. Analyze complex datasets to uncover clear, actionable insights that shape product direction. Partner with go-to-market teams to demonstrate the technical and business value of our products to customers. Qualifications 3-5 years of total experience, including at least 2-3 years working deeply with product analytics, experimentation, or data-driven products. Strong proficiency in SQL and Python. Hands-on experience with product analytics, experimentation frameworks, or backtesting methodologies. Skilled in designing, building, and maintaining dashboards and core product performance metrics. Capable of designing and interpreting backtests or offline evaluations for ML and rules-based systems. Excellent communicator with strong stakeholder-management skills across diverse teams. Background in fraud or risk domains - Nice to have. Familiarity with data-insights products and a solid understanding of model-performance metrics - Nice to have. Exposure to customer-facing or GTM-facing analytics - Nice to have. The target base salary for this position ranges from $162,000/year to $222,000/year in Zone 1. The target base salary will vary based on the job's location. Our geographic zones are as follows:Zone 1 - New York City and San Francisco Bay AreaZone 2 - Los Angeles, Seattle, Washington D.C.Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San DiegoZone 4 - Raleigh-Durham and all other US cities Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here.

**Dir Full Stack Data Scientist** As an Associate Director, you will lead and deliver cross-functional Data Science capabilities as a Full Stack Data Scientist in support of R&D Data Science needs. Your role will involve coordinating necessary activities and being hands-on in delivering analytics stacks for R&D as part of the DSAI-DDRC team. You will manage the technology stack, including platforms, applications, integration tools, and analytics tools supporting R&D processes. Additionally, you will coordinate work with external analytics developers, guide product team members, and strategize, deliver, and execute tasks. Responsibilities include managing issue analysis, triage, planning, communication of timelines, and analytic tool delivery. **YOUR TASKS AND RESPONSIBILITIES:** + Design, develop, and maintain full stack applications to support R&D initiatives; + Collaborate with data scientists, ML engineers, and domain experts to translate research prototypes into production-ready tools; + Build intuitive user interfaces and robust backend systems for data visualization, model interaction, and experimentation; + Develop APIs and microservices to integrate with internal platforms and external data sources; + Optimize performance, scalability, and reliability of R&D tools and applications; + Participate in architectural discussions and contribute to technical strategy for R&D software infrastructure; + Rapidly prototype new ideas and iterate based on feedback from researchers and stakeholders; + Coordinate work conducted by external analytics developers; + Provide expert guidance to product team members for strategy, delivery, and execution; + Manage issue analysis, triage, and assignment; plan and communicate timelines and deployments. **WHO YOU ARE** Bayer seeks an incumbent who possesses the following: + MSc in statistics, mathematics, informatics, computer sciences, ML Ops, Computer Engineering, or similar education; + Proficiency in frontend technologies: React, Angular, or Vue.js; + Strong experience with backend frameworks: Node.js, Python (Flask, FastAPI, Django), or Java; + Solid understanding of RESTful APIs, GraphQL, and WebSockets; + Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes); + Familiarity with CI/CD pipelines, Git, and agile development practices; + Knowledge of database systems: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis); + Ability to work in a collaborative, interdisciplinary team environment; + Experience in GxP/CSV & IT project or business process design; + Extensive experience in Data Science capability assessment and analysis; + Preferred project management experience; + Demonstrated ability to address and resolve conflicts; proven collaboration skills; + Pharma and life sciences experience, security and compliance experience; + Exposure to machine learning workflows or experience integrating ML models into applications; + Experience with data visualization libraries (D3.js, Plotly, etc.); + Understanding of MLOps or model deployment practices; + Background in scientific computing, data engineering, or experimental software development; + Demonstrated ability to lead through influence in a cross-functional team; + Passion for digital transformation, change, and a play-to-win attitude. The incumbent for this position will be located in the US, UK or Germany. This posting will be available for application until 10/24/2025. Employees can expect to be paid a salary between $141,790 to $212,685. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.. This salary range is merely an estimate and may vary based on an applicant's location, market data/ranges, an applicant's skills and prior relevant experience, certain degrees and certifications, and other relevant factors. \#LI Bayer is an Equal Opportunity Employer/Disabled/Veterans Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Job postings will remain open for a minimum of ten business days and are subject to immediate closure thereafter without additional notice. **Division:** Pharmaceuticals **Reference Code** 852197 **Functional Area:** Information Technology **Location:** US, UK or Germany **Employment Type:** Regular **Position Grade:** VS 2.0 **Contact Us** AddressTelephone **Creve Coeur, MO** *****************, option #5** **63167** OR **Submit a ticket via** **the self-service option by visiting** go/askhr

About the Role We are seeking a highly capable Data Scientist to build and operationalize advanced analytics and machine learning capabilities that directly support national security missions. You will work closely with mission analysts, engineers, and operators to convert complex data into actionable intelligence, predictive insights, and measurable results. This is a hands-on position where you will take ownership of the entire data science lifecycle, from data exploration and model development through secure deployment and continuous improvement. You will combine strong analytical expertise with engineering discipline to deliver reliable, mission-ready solutions. Key Responsibilities Design and implement analytical models and algorithms that drive mission outcomes Develop and deploy production-grade machine learning pipelines in secure, operational environments Collect, process, and analyze large, diverse datasets to uncover trends and improve decision-making Build and automate end-to-end data workflows that support continuous delivery of insights Collaborate with cross-functional teams to translate mission requirements into technical data solutions Enhance system reliability through model monitoring, validation, and performance reporting Present analytical findings clearly and effectively to both technical and operational audiences Required Qualifications Active TS/SCI clearance (with Full Scope Polygraph) Bachelors or Masters degree in Data Science, Computer Science, Mathematics, or a related field (or equivalent experience) Proven experience applying data science and machine learning to real-world operational or mission-focused challenges Strong proficiency in Python and data science libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch Experience with SQL and distributed data processing tools such as Spark or Dask Solid understanding of statistics, model validation, and data governance principles Proficiency with Linux environments and Git-based version control systems Proven experience deploying analytical solutions securely and at scale Nice to Have Familiarity with R or Julia for advanced statistical analysis Experience using cloud-based ML platforms such as AWS SageMaker, Azure ML, or GCP Vertex AI Knowledge of MLOps practices, containerization, and orchestration (Docker, Kubernetes) Background in natural language processing, computer vision, or time-series analysis Whats on Offer? Contribute directly to national security missions through data-driven innovation Highly competitive salary with clearance retention incentives Access to advanced analytical and compute infrastructure in secure environments Ongoing professional development, training, and certification support Required Skills: Spring Incentives Kafka Analysts Gcp Operators Data Processing Operations RabbitMQ CI/CD Azure Version Control Salary Microservices Spring Boot AWS Reliability Architecture Kubernetes Automation Docker Linux Computer Science Security Software Java Design Engineering Python Science Training

Join our Global Payments & Liquidity (GPL) team as a Vice President-level Lead Data Scientist, where you'll shape the future of data-driven decision-making in one of the most dynamic areas of financial services. This is a high-impact leadership role for an innovative thinker who thrives on solving complex problems and delivering scalable solutions that transform customer experiences and accelerate business growth. What You'll Do Drive Strategy Through Data: Partner with senior business leaders to translate strategic priorities into actionable data science initiatives that influence product innovation and customer engagement. Lead Advanced Modeling: Design and implement sophisticated machine learning and deep learning models, leveraging cutting-edge statistical techniques to uncover insights and predict outcomes. Architect Scalable Solutions: Collaborate with data engineering teams to ensure robust, secure, and production-ready deployment of analytics solutions across cloud platforms. Champion Data Excellence: Establish and enforce best practices for data quality, governance, and reproducibility, ensuring models meet the highest standards of accuracy and transparency. Communicate Impact: Present complex findings in a clear, compelling way to both technical and non-technical stakeholders, driving informed decisions at the executive level. Required Qualifications: 5+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 5+ years experience in Python and SQL 1+ years experience in leadership or mentorship of more junior team members Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Preferred Qualifications Expertise in deep learning frameworks (TensorFlow, PyTorch) and experience with NLP or predictive modeling. Prior experience supporting Agile product teams in a corporate environment. Familiarity with banking products, transaction services, and working capital solutions. Knowledge of cloud platforms (AWS, Azure) and data visualization tools (Power BI, Tableau). Why Join Us? Influence strategic decisions at the intersection of data science and global payments. Work on high-visibility projects that shape the future of financial technology. Competitive compensation and relocation support for candidates outside Charlotte, NC. Posting End Date: 30 Jan 2026 *Job posting may come down early due to volume of applicants. We Value Equal Opportunity Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. Applicants with Disabilities To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo. Drug and Alcohol Policy Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more. Wells Fargo Recruitment and Hiring Requirements: a. Third-Party recordings are prohibited unless authorized by Wells Fargo. b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings. Responsibilities: Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development. Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry's business objectives. Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models. Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment. Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications. Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team's technical capabilities. Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment. Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development. Requirements: A bachelor's degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs). Experience with multimodal data processing (e.g., combining text, image, and 3D data). Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. Strong background in probability, statistics, and optimization techniques relevant to generative modeling. Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker). Familiar with software engineering principles, including version control, reproducibility, and continuous integration. Experience in the manufacturing, supply chain, or similar industries is a plus. The estimated base salary range for new hires into this role is $164,000- $213,000 annually + annual bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more. #LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Job Description Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings. Responsibilities: Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development. Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry's business objectives. Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models. Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment. Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications. Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team's technical capabilities. Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment. Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development. Requirements: A bachelor's degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs). Experience with multimodal data processing (e.g., combining text, image, and 3D data). Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. Strong background in probability, statistics, and optimization techniques relevant to generative modeling. Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker). Familiar with software engineering principles, including version control, reproducibility, and continuous integration. Experience in the manufacturing, supply chain, or similar industries is a plus. The estimated base salary range for new hires into this role is $164,000- $213,000 annually + annual bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more. #LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

This role is based remotely but if you live within a 50-mile radius of an office [Atlanta, Austin, Detroit, Warren, or Mountain View], you are expected to report to that location three times a week, at minimum. The Role The Senior Data Scientist is an internal expert on methodology and practice of marketing analytics. This individual has deep technical expertise in Media Mix Modeling (MMM), with hands-on experience developing custom econometrics and statistical models that quantify media impacts and optimize market investment. The Data Scientist has expertise in the economics of media channels (e.g., Linear/Addressable TV, Online Display, Paid Search, Social), measurement of ROAS lift, coordination of media tactics (sequencing/ frequency caps), and insourcing of off-the-shelf MMM solutions. This person will work closely with GM brand stakeholders to ensure business acceptance of proposed methods, objective performance evaluation, and effective media activation that drives sales. This person will be responsible for developing Media Mix Models, drawing insights, and creating scalable products that identify channel and tactic level high return on investment. Fully qualified individual contributor who has knowledge and understanding of all aspects of a function and exercises independent discretion and judgment on significant matters based on professional knowledge. Level most professionals can expect to achieve in their career. EXPERTISE Recognized as a fully qualified, experienced professional. Has complete knowledge and full understanding of own area and broad knowledge of related areas. Takes broad challenges and, through independent professionally developed analysis, identifies and analyses options, and breaks them down into initiatives capable of implementation. Identifies opportunities and proposes solutions to improve internal processes, services, and structures to support functional strategies. Uses advanced analytical and problem-solving techniques to resolve a wide range of non-standard problems. Works independently; receives minimal guidance. Acts as a resource for colleagues with less experience. COMPLEXITY Identifies and devises solutions based on limited information and precedent. Uses evaluation and judgement to solve problems that are new to the organization and require a deep level of experience and strategic thought to create a solution. Enhances relationships and networks with senior internal/external partners who are not familiar with subject matter and often require persuasion. Uses data and analysis to demonstrate the value of a project, anticipating, and addressing objections and or concerns. Often effects change in broader functional area without direct exercise of command, using persuasion in situations where reaching agreement may be hindered by differing opinions, past practices, or experiences. SCOPE AND IMPACT Challenges and problems are of a diverse scope with multiple moving parts, where developing a plan and viewing the whole picture is a significant challenge itself. Work is done independently and is reviewed at critical points. Owns the development and delivery of solutions, driving cross team and group efforts. Leads by example, taking responsibility for their own actions, acknowledging mistakes, and holding themselves accountable for achieving goals. Addresses and evaluates a diverse range of issues using innovative methods and proposing alternative approaches. Serves as a mentor to more junior level employees, providing coaching and guidance on difficult issues. Has significant operational impact across their function. What You'll Do Work on a cross-functional team to propose and implement high-impact, data-driven solutions to address business challenges across a variety of business units Apply advanced data-driven modeling techniques to inform decision making and solve complex business problems: Create breakthrough solutions, performing exploratory and targeted data analyses Undertake preprocessing of structured and unstructured data Monitor and sustain model effectiveness Present complex information using data visualization techniques Work with diverse technical teams and provide data and analytical oversight to ensure project deliverables fulfill business needs and timing Identify long-term technical innovations while continuously improving execution efficiency Possessing contextual business knowledge and functional domain expertise in the advertising and media space, showing a proven ability of using data, analytics, and insights to add revenue and business-impacting value in this via audience selection and behavioral engagement. Deep knowledge of marketing media modeling techniques, including MMM, MTA, unified attribution, ROAS level testing, and various industry measurement media platforms. Exhibiting a perspective of constrained curiosity, asking why, and suggesting experimentation to drive incremental impact. Exhibiting the ability to tell a succinct, data-driven story in any forum and tailor delivery to a wide range of stakeholder levels, from analyst to senior executive. Ensuring a superior level of delivery quality at all levels of their organization through the creation of internal structures and extensible frameworks to manage accountability and develop staff. Your Skills & Abilities (Required Qualifications) Minimum five years of experience developing, deploying, and monitoring performance of media mix or related models Proficient writing Python/R (modeling) and SQL/Spark (data), working with PYMC, StatsModels, Spark/ML, sklearn, numpy and related packages Desired expertise media mix modeling (MMM), multi-touch attribution (MTA), consumer choice (multinomial logit), time-series forecasting, hierarchical bayes, panel-data methods (fixed/random effects), censored/truncated regressions, selection models, non-random treatment effects, item response theory, latent class regression Prior experience with paid, earned, and owned media Ability to prioritize and manage multiple tasks and projects at once without sacrificing quality What Can Give You a Competitive Advantage (Preferred Qualifications) Advanced degree (M.A./Ph.D. preferred) in Marketing Data Science, Econometrics, Operations Research, Psychometrics, Finance, (Bio) Statistics, or another quantitative field This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate. Compensation: The expected base compensation for this role is: $130,800 - $211,200. Actual base compensation within the identified range will vary based on factors relevant to the position. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.) #LI-CC1 About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at ************. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

We are searching for a Staff Safety Data Scientist on the Safety Analysis team who is a technical leader and go-to expert for risk and safety guidance, leveraging deep expertise in data science to lead critical safety research. Your insights will drive the safety strategy and external safety communications, including the development of industry-leading, benchmark safety studies and frameworks. The role requires a strong background in risk and hazard assessment and exceptional communication and interpersonal skills. You will be responsible for applying advanced statistical analysis and probabilistic modeling to support the safety case, inform hardware and software decisions, and identify critical risk factors. You will collaborate with diverse stakeholders across engineering, operations, and product. In This Role, You Will: Lead the development of novel quantitative data analytics using both proprietary (Aurora-logged, sensor, system, integration testing data) and publicly available data (CRSS, FARS, state-level information). Author and present technical analyses and findings to diverse internal and external audiences, including stakeholders, authoritative bodies, and industry forums. Design and automate data collection and analysis to support ongoing safety programs. Extract insights from historical system safety performance to develop leading indicators for future performance forecasting. Analyze safety data from operational vehicles, crash metrics, and near-miss incidents to inform safety strategies and decision-making. Develop statistical models and algorithms to predict potential risks and prevent incidents, improving the safety performance of autonomous systems. Model self-driving vehicle behaviors at the system and subsystem levels. Develop and maintain reports and expressions of baseline risk coverage and application in operations. Design and develop expressions of risk benchmarking from similar industries. Create dashboards and reports for communicating risk, ranking, and anomalies. Present safety research findings to senior leadership and recommend actionable improvements to safety protocols and operational systems. Mentor and lead junior team members, fostering their professional growth. Required Qualifications Bachelor's degree in Data Science, Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience. 7+ years of progressive experience solving large-scale complex problems. Demonstrated experience in a safety related domain (e.g., transportation, aerospace, robotics, medical devices). Strong understanding of safety principles and risk assessment methodologies; with a proven track record of using data science techniques to solve safety challenges and mitigate risks in a dynamic environment. Deep command of statistical methods, probabilistic modeling, and performing rapid exploratory data analysis. Expertise in data science tools (e.g., Python, SQL, R), statistical modeling, machine learning, predictive analytics, and visualization software (e.g., Tableau, Power BI). Adept at querying, analyzing, and visualizing large datasets. Excellent communication and presentation skills, with the ability to convey complex information to various audiences. Strong leadership skills, with the ability to provide guidance and mentorship. Ability to work independently, as part of a cross-functional team, or as a project lead. Desirable Qualifications Advanced degree in Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience. Experience working in safety and risk, ideally complemented by a portfolio of publications, reports, or conference presentations. Familiarity with rapidly scaling operational environments. Proficient in working with advanced data transformation tools such as DBT. Skilled in building and deploying using Amazon Web Services (AWS) tools. Background in the Autonomous Vehicles, Aerospace, or Robotics domains. The base salary range for this position is $171,000 - $247,000 per year. Aurora's pay ranges are determined by role, level, and location. Within the range, the successful candidate's starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

Job DescriptionAre you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list. Pattern accelerates brands on global ecommerce marketplaces leveraging proprietary technology and AI. Utilizing more than 46 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of ecommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting and customer service. Hundreds of global brands depend on Pattern's ecommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces-including Amazon, Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre. To learn more, visit pattern.com or email *****************. Pattern has been named one of the fastest growing tech companies headquartered in North America by Deloitte and one of best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek's Global Most Loved Workplaces . We need a RevOps Data Scientist to help Pattern improve and scale their data operations. This role will play a crucial role aiding the both the data science and revenue operations teams, giving them visibility into key business units and stakeholders. This is a full-time role and will work a hybrid schedule based in Lehi, UT.What is a day in the life of a Data Scientist? Building upon and improving existing analytical frameworks. Refining operational processes to increase both accuracy and reliability. Scaling machine learning models to support business growth and new demands. Leveraging global market data and trends to train and evolve models. Simplifying workflows and optimizing systems for maximum efficiency. What will I need to thrive in this role? Bachelor's Degree. 2-3 years of experience as a Data Scientist, Data Analyst, or a Data Engineer. Excellent communication skills with the ability to work cross-functionally across marketing, rev ops, data science, and sales engineering teams. Strength in data architecture and efficiency, backed by a strong engineering background. Deep experience with AWS (EC2, ECS) and relevant AWS certifications. Proficiency in Python and SQL, with the capability to collaborate closely with software and sales engineering teams (“the kitchen”). Demonstrated aptitude and proficiency in AI, with a track record of expanding AI capabilities. Experience expanding existing frameworks. Ability to enhance accuracy and precision in operational processes. Proven track record of scaling models to accommodate growth and increased demand. Experience training systems with global patterns and market share data. Expertise in streamlining processes to achieve greater efficiency. What does high performance look like? You follow through with all assignments in a timely manner with minimal supervision You give 100% to all tasks and projects you are given. You actively comment and participate in group collaborations. You take full ownership of your projects and follow through to completion. You facilitate team education through training and cross-functional transparency What is my potential for career growth? Career growth opportunities are available for RevOps Data Scientists, with leadership roles potentially on the horizon based on tenure and performance. What is the team like? You will be supervised by Nate Winn, RevOps Data Science Manager. This team is data driven and results oriented. You will collaborate regularly with members of your team to implement actionable solutions. Ideas and input are encouraged from all members. Sounds great! What's the company culture? Game Changers- A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches a realistic timeline to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern's processes and outcomes. Data Fanatics- A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of the solutions using data. Partner Obsessed- An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner's expectations, and delivers results that exceed them, prioritizes the needs of your partners, and takes the time to create a personable experience for those interacting with Pattern. Team of Doers- Someone who is a part of a team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners. What is the hiring process? Initial phone interview with Pattern's talent acquisition team. Technical interview with a hiring manager and peer (Zoom). Technical interview with a hiring manager. Final interview with an executive. References. Offer. How can I stand out as an applicant? Discuss professional accomplishments with specific data to quantify examples. Provide insights on how you can add value and be the best addition to the team. Focus on mentioning how you would be partner obsessed at Pattern. Share experience on any side projects related to data and analytics. Why should I work at Pattern? Pattern offers big opportunities to make a difference in the ecommerce industry! We are a company full of talented people that evolves quickly and often. We set big goals, work tirelessly to achieve them, and we love our Pattern community. We also believe in having fun and balancing our lives, so we offer awesome benefits that include: - Unlimited PTO- Paid Holidays- Onsite Fitness Center- Company Paid Life Insurance- Casual Dress Code- Competitive Pay- Health, Vision, and Dental Insurance- 401(k) match. Pattern matches 100% of the first 3% in eligible compensation deferred and 50% of the next 2% in eligible compensation deferred. Pattern provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability, status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Aurora is working to deliver the benefits of self-driving technology safely, quickly, and broadly. We are searching for a Senior Safety Data Scientist to support the development of quantitative safety arguments and tooling infrastructure. You will apply statistical analysis, machine learning, and probabilistic modeling to inform safety strategy and support external safety communications. You will collaborate with stakeholders across software, systems, hardware, data science, data infrastructure, operations, product, legal, and government relations to shape the future of autonomous vehicle safety. In This Role, You Will: Design and deploy safety related data pipelines, models, tooling, and infrastructure in partnership with technical and non-technical stakeholders. Execute in-depth safety analysis on operational and simulation data, distilling complex findings into immediate, actionable risk mitigation strategies. Implement safety-related initiatives in alignment with safety goals and best practices. Develop safety related processes and reporting for organizational, operational, and product data to ensure accuracy and consistency. Support the identification of systemic, latent, and emerging risks in fleet operations to advance root cause analyses and implement appropriate risk management measures. Define and evolve safety metrics by designing and validating novel measures using hypothesis testing and exploratory analysis. Audit and validate technical safety evidence and artifacts spanning the breadth of self-driving technology (hardware, software, and operations) to ensure alignment with quantitative safety arguments and regulatory standards through enterprise tool suites Conduct root cause analysis for safety issues and support the formulation of specific, data-backed corrective actions. Lead the quantitative development of internal and external reports (e.g., Voluntary Safety Self Assessment) and public statements, ensuring safety arguments are statistically robust. Present and expertly communicate the output of technical analysis to both technical and non-technical audiences. Development of new processes and procedures related to safety metrics, data integrity, and issue handling. Required Qualifications Bachelor's/Master's degree in Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent technical experience. 5+ years of industry experience solving complex problems Proficiency in programming languages such as Python and R Experience building and deploying models using Amazon Web Services (AWS) tools, e.g. AWS Bedrock, Redshift Experience working with data transformation tools such as DBT Knowledge and experience with relational databases (SQL) and data warehouses Strong skills for querying, analyzing, and visualizing large datasets Expertise in applied statistics, exploratory data analysis, hypothesis testing, and probabilistic modeling Experience in machine learning techniques Effective written and verbal communication skills to present work with, and present technical analysis to, both technical and non-technical audiences Ability to work independently and as part of a cross-functional team Desirable Qualifications Experience working in a safety-related domain Knowledge of automotive domain and relevant safety standards Experience in the Autonomous Vehicles, Aerospace, or Robotics domains The base salary range for this position is $146,000 - $211,500 per year. Aurora's pay ranges are determined by role, level, and location. Within the range, the successful candidate's starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. #LI-SP1 #Mid-Senior

About the role: The Senior Data Scientist will bring rigor to strategic initiatives across the Support Organization. As a Senior Data Scientist, you will be a core technical contributor to our Data Science and Analytics team with deep expertise in driving data-driven decision-making, data querying/munging, data visualization, and predictive analytics. You will work closely with Support, Product, and technical teams to translate business questions into quantitative analysis and deliver data-driven strategies. This role is open to candidates residing in the US except the San Francisco Bay Area (125 mi. radius from 1 De Haro St, San Francisco) and NYC Metro Area (50 mi. radius from 131 W 55th St, New York). You should apply if: You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact-helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely. You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations. You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go. You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes. You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we're all racing toward our connected operations vision, and we intend to win-together. In this role, you will: Translate data into strategic insights via memos, presentations, dashboards, etc. to support decision-making for operational and leadership teams Building analytical models to identify patterns, anomalies, and root causes (e.g., analyzing ticket data to proactively identify common customer issues) Design and run A/B and other experiments and tests to evaluate AI solutions Build relationships with technical and non-technical stakeholders to understand data structures and business priorities Leverage SQL, Python/R to shape and analyze data Build a strong sense of product and data acumen (e.g. customer experience, data logging) Stay connected to industry and academic research and adopt novel technology that suits Samsara's needs Champion, role model, and embed Samsara's cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices Minimum requirements for the role: Advance degree in Statistics or other quantitative field (e.g., Applied Math, Engineering, Computer Science, Physics, etc.) 8+ years experience in a data-related role relevant (data science, data analyst, business analytics, business intelligence) Proficiency in data manipulation and processing in SQL, Python, and/or R Experience building statistical and other analytical models, preferably in Python or R Ability to communicate trends and learnings via data visualizations including Tableau Ability to effectively share project statuses and take ownership of tasks while handling competing priorities Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge Curious about our data, our product and excited to have an impact An ideal candidate also has: PhD in Statistics or other quantitative field Ability to scale models into automated pipelines A strong track record of cross-functional partnership Record of successful mentoring and development of team members Experience working with large datasets using distributed computing (e.g., Spark, Hive)