Data scientist jobs in Concord, CA

Key Responsibilities Design and productionize models for opportunity scanning, anomaly detection, and significant change detection across CRM, streaming, ecommerce, and social data. Define and tune alerting logic (thresholds, SLOs, precision/recall) to minimize noise while surfacing high-value marketing actions. Partner with marketing, product, and data engineering to operationalize insights into campaigns, playbooks, and automated workflows, with clear monitoring and experimentation. Required Qualifications Strong proficiency in Python (pandas, NumPy, scikit-learn; plus experience with PySpark or similar for large-scale data) and SQL on modern warehouses (e.g., BigQuery, Snowflake, Redshift). Hands-on experience with time-series modeling and anomaly / changepoint / significant-movement detection(e.g., STL decomposition, EWMA/CUSUM, Bayesian/prophet-style models, isolation forests, robust statistics). Experience building and deploying production ML pipelines (batch and/or streaming), including feature engineering, model training, CI/CD, and monitoring for performance and data drift. Solid background in statistics and experimentation: hypothesis testing, power analysis, A/B testing frameworks, uplift/propensity modeling, and basic causal inference techniques. Familiarity with cloud platforms (GCP/AWS/Azure), orchestration tools (e.g., Airflow/Prefect), and dashboarding/visualization tools to expose alerts and model outputs to business users.

An early-stage investment of ours is looking to make their first IC hire in data science. This company builds tools that help teams understand how their AI systems perform and improve them over time (and they already have a lot of enterprise customers). We're looking for a Sr Data Scientist to lead analytics for sales, marketing, and customer success. The job is about finding insights in data, running analyses and experiments, and helping the business make better decisions. Responsibilities: Analyze data to improve how the company finds, converts, and supports customers Create models that predict lead quality, conversion, and customer value Build clear dashboards and reports for leadership Work with teams across the company to answer key questions Take initiative, communicate clearly, and dig into data to solve problems Try new methods and tools to keep improving the company's GTM approach Qualifications: 5+ years related industry experience working with data and supporting business teams. Solid experience analyzing GTM or revenue-related data Strong skills in SQL and modern analytics tools (Snowflake, Hex, dbt etc.) Comfortable owning data workflows-from cleaning and modeling to presenting insights. Able to work independently, prioritize well, and move projects forward without much direction Clear thinker and communicator who can turn data into actionable recommendations Adaptable and willing to learn new methods in a fast-paced environment About Us: Greylock is an early-stage investor in hundreds of remarkable companies including Airbnb, LinkedIn, Dropbox, Workday, Cloudera, Facebook, Instagram, Roblox, Coinbase, Palo Alto Networks, among others. More can be found about us here: ********************* How We Work: We are full-time, salaried employees of Greylock and provide free candidate referrals/introductions to our active investments. We will contact anyone who looks like a potential match--requesting to schedule a call with you immediately. Due to the selective nature of this service and the volume of applicants we typically receive from our job postings, a follow-up email will not be sent until a match is identified with one of our investments. Please note: We are not recruiting for any roles within Greylock at this time. This job posting is for direct employment with a startup in our portfolio.

We're working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics. We're seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability. This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions. Key Responsibilities Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records) Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers Research and prototype innovative approaches leveraging both classical and modern machine learning techniques Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments Collaborate cross-functionally with data engineers, clinicians, and product teams to ensure models address real-world healthcare needs Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations Required Qualifications Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.) Proven track record of transitioning models from research prototypes to production systems Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued) Bonus Qualifications Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC) Background in actuarial modeling, claims forecasting, or risk adjustment methodologies

Lead Data Scientist - Computer Vision/Image Processing About the Role We are seeking a Lead Data Scientist to drive the strategy and execution of data science initiatives, with a particular focus on computer vision systems & image processing techniques. The ideal candidate has deep expertise in image processing techniques including Filtering, Binary Morphology, Perspective/Affine Transformation, Edge Detection. Responsibilities Solid knowledge of computer vision programs and image processing techniques: Filtering, Binary Morphology, Perspective/Affine Transformation, Edge Detection Strong understanding of machine learning: Regression, Supervised and Unsupervised Learning Proficiency in Python and libraries such as OpenCV, NumPy, scikit-learn, TensorFlow/PyTorch. Familiarity with version control (Git) and collaborative development practices

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow's ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries. ******NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future*** Summary: The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Job Responsibilities: • Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. • Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. • Generate and test hypotheses and analyze and interpret the results of product experiments. • Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation. • Provide Business Intelligence (BI) and data visualization support, which includes, but limited to support for the online customer service dashboards and other ad-hoc requests requiring data analysis and visual support. Skills: • Experienced in either programming languages such as Python and/or R, big data tools such as Hadoop, or data visualization tools such as Tableau. • The ability to communicate effectively in writing, including conveying complex information and promoting in-depth engagement on course topics. • Experience working with large datasets. Education/Experience: • Master of Science degree in computer science or in a relevant field.

Net2Source is a Global Workforce Solutions Company headquartered at NJ, USA with its branch offices in Asia Pacific Region. We are one of the fastest growing IT Consulting company across the USA and we are hiring " Senior Data Scientist " for one of our clients. We offer a wide gamut of consulting solutions customized to our 450+ clients ranging from Fortune 500/1000 to Start-ups across various verticals like Technology, Financial Services, Healthcare, Life Sciences, Oil & Gas, Energy, Retail, Telecom, Utilities, Technology, Manufacturing, the Internet, and Engineering. Position: Senior Data Scientist Location: Pleasanton, CA (Onsite) - Locals Only Type: Contract Exp Level - 10+ Years Required Skills Design, develop, and deploy advanced marketing models, including: Build and productionize NLP solutions. Partner with Marketing and Business stakeholders to translate business objectives into data science solutions. Work with large-scale structured and unstructured datasets using SQL, Python, and distributed systems. Evaluate and implement state-of-the-art ML/NLP techniques to improve model performance and business impact. Communicate insights, results, and recommendations clearly to both technical and non-technical audiences. Required Qualifications 5+ years of experience in data science or applied machine learning, with a strong focus on marketing analytics. Hands-on experience building predictive marketing models (e.g., segmentation, attribution, personalization). Strong expertise in NLP techniques and libraries (e.g., spa Cy, NLTK, Hugging Face, Gensim). Proficiency in Python, SQL, and common data science libraries (pandas, NumPy, scikit-learn). Solid understanding of statistics, machine learning algorithms, and model evaluation. Experience deploying models into production environments. Strong communication and stakeholder management skills. Why Work With Us? We believe in more than just jobs-we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter. Our Commitment to Inclusion & Equity Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics. Awards & Recognition America's Most Honored Businesses (Top 10%) Fastest-Growing Staffing Firm by Staffing Industry Analysts INC 5000 List for Eight Consecutive Years Top 100 by Dallas Business Journal Spirit of Alliance Award by Agile1 Maddhuker Singh Sr Account & Delivery Manager ***********************

Our Mission At Palo Alto Networks everything starts and ends with our mission: Being the cybersecurity partner of choice, protecting our digital way of life. Our vision is a world where each day is safer and more secure than the one before. We are a company built on the foundation of challenging and disrupting the way things are done, and we're looking for innovators who are as committed to shaping the future of cybersecurity as we are. Who We Are We take our mission of protecting the digital way of life seriously. We are relentless in protecting our customers and we believe that the unique ideas of every member of our team contributes to our collective success. Our values were crowdsourced by employees and are brought to life through each of us everyday - from disruptive innovation and collaboration, to execution. From showing up for each other with integrity to creating an environment where we all feel included. As a member of our team, you will be shaping the future of cybersecurity. We work fast, value ongoing learning, and we respect each employee as a unique individual. Knowing we all have different needs, our development and personal wellbeing programs are designed to give you choice in how you are supported. This includes our FLEXBenefits wellbeing spending account with over 1,000 eligible items selected by employees, our mental and financial health resources, and our personalized learning opportunities - just to name a few! At Palo Alto Networks, we believe in the power of collaboration and value in-person interactions. This is why our employees generally work full time from our office with flexibility offered where needed. This setup fosters casual conversations, problem-solving, and trusted relationships. Our goal is to create an environment where we all win with precision. Job Description Your Career As a Staff Data Engineer and Scientist, you will be an integral member of our Customer Analytics team, responsible for shaping the future of our business operations through robust data infrastructure and advanced analytical solutions. This unique hybrid role combines data engineering and applied AI/ML, requiring an entrepreneurial problem-solver who thrives in tackling ambiguous business problems through their deep understanding of the business as well as deep technical expertise. You will act as both a strategic partner as well as builder, developing deep insights , building, developing and curating new datasets, as well as owning the end to end ML/AI model deployment for key customer success initiatives. You will be constantly challenged by tough engineering and design tasks, working in a fast-paced setting to deliver high-quality, impactful work. This is an in office role 3 days/week in our HQ, Santa Clara, CA Your Impact In this versatile role, you will drive impact across both data engineering and data science domains: Data Engineering Foundations Design & Development: Design and implement scalable data architectures and datasets that support the organization's evolving data needs, providing the technical foundations for our analytics team and business users. Data Engineering: Support and implement large datasets in batch/real-time analytical solutions leveraging data transformation technologies. Data Security & Scalability: Enable robust data-level security features and build scalable solutions to support dynamic cloud environments, including financial considerations. Process Improvement: Perform code reviews with peers and make recommendations on how to improve our end-to-end development processes. AI/ML Innovation & Business Impact Develop & Deploy Classical ML Models: Own the end-to-end lifecycle of machine learning projects. You'll build and productionize sophisticated models for critical business areas such as marketing attribution, customer churn prediction, case escalation and other relevant use-cases to post-sales. Optimize AI Agentic Systems: Play a key role in our generative AI initiatives. You will be responsible for characterizing, evaluating, and fine-tuning AI agents-such as conversational systems that allow users to query massive datasets using natural language-to improve their accuracy, efficiency, and reliability. Partner with Business Stakeholders: Act as an internal consultant to our Go-to-Market (GTM), Global Customer Services (GCS) and Product and Finance teams. You'll translate business challenges into data science use-cases, identify opportunities for AI-driven solutions, and present your findings in a clear, actionable manner. Own the Full Data Science Lifecycle: Your responsibilities will cover the entire project workflow, working with the business to understand the problem, charting a path to solve the problem, feature engineering, model selection and training, robust evaluation, deployment, and, in partnership with the data platform team, ongoing monitoring for performance degradation. Qualifications Your Experience 7 plus years experience building and maintain data pipeline both for reporting, analysis and feature engineering. Experience building and optimizing clean, well-structured analytical datasets for business and data science use cases. This includes Implementing and supporting Big Data solutions for both batch (scheduled) and real-time (streaming) analytics. Prior experience working extensively within dynamic cloud environments, specifically Google Cloud Services (GCS) BigQuery and Vertex AI. Prior experience developing dashboards in Tableau/Looker or similar data viz platform. Nice to have: Experience implementing and managing data-level security features to ensure data is protected and access is properly controlled. Expert-level programming skills in Python and familiarity with core data science and machine learning libraries (e.g., Scikit-learn, Pandas, PyTorch/TensorFlow, XGBoost). A solid command of SQL for complex querying and data manipulation. Proven ability to work autonomously, navigate ambiguity, and drive projects from concept to completion. Preferred Qualifications Prior working experience in Customer Analytics space and customer experience use-cases, e.g. Escalation, Risk predictors, Renewals and efficiency of project delivery in Professional Services space. Direct experience with generative AI, including hands-on work with LLMs and frameworks like LangChain, LlamaIndex, or the Hugging Face ecosystem. Experience in evaluating and optimizing the performance of AI systems or agents. Demonstrated expertise in specialized modeling domains such as causal inference, time-series analysis. An MS or PhD in a quantitative field like Computer Science, AI, Statistics, or equivalent practical experience or equivalent military experience. Additional Information The Team Working at a high-tech cybersecurity company within Information Technology is a once-in-a-lifetime opportunity. You'll join the brightest minds in technology, creating, building, and supporting tools and enabling our global teams on the front line of defense against cyberattacks. We're connected by one mission but driven by the impact of that mission and what it means to protect our way of life in the digital age. Join a dynamic and fast-paced team of people who feel excited by the prospect of a challenge and feel a thrill at resolving technical gaps that inhibit productivity. Compensation Disclosure The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $143000- $231000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here. Our Commitment We're problem solvers that take risks and challenge cybersecurity's status quo. It's simple: we can't accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Elevate Data Engineer Hybrid, CA Brooksource is searching for an Associate Data Engineer to join our HealthCare partner to support their data analytics groups. This position is through Brooksource's Elevate Program, and will include additional technical training including, but not limited to: SQL, Python, DBT, Azure, etc. Responsibilities Assist in the design, development, and implementation of ELT/ETL data pipelines using Azure-based technologies Support data warehouse environments for large-scale enterprise systems Help implement and maintain data models following best practices Participate in data integration efforts to support reporting and analytics needs Perform data validation, troubleshooting, and incident resolution for data pipelines Support documentation of data flows, transformations, and architecture DevOps & Platform Support Assist with DevOps activities related to data platforms, including deployments and environment support Help build and maintain automation scripts and reusable frameworks for data operations Support CI/CD pipelines for data engineering workflows Assist with monitoring, alerting, and basic performance optimization Collaborate with senior engineers to support infrastructure-as-code and cloud resource management Collaboration & Delivery Work closely with data engineers, solution leads, data modelers, analysts, and business partners Help translate business requirements into technical data solutions Participate in code reviews, sprint planning, and team ceremonies Follow established architecture, security, and data governance standards Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience) Foundational knowledge of data engineering concepts, including ETL/ELT and data warehousing Experience or coursework with SQL and relational databases Familiarity with Microsoft Azure or another cloud platform Basic scripting experience (Python, SQL, PowerShell, or Bash) Understanding of version control (Git) Preferred / Nice-to-Have Skills Exposure to Azure services such as Azure Data Factory, Synapse Analytics, Azure SQL, or Data Lake Basic understanding of CI/CD pipelines and DevOps concepts Familiarity with data modeling concepts (star schema, normalization) Experience of fa Interest in automation, cloud infrastructure, and reliability engineering Internship or project experience in data engineering or DevOps environments

This will be a data engineer role for processing battery testing data to facilitate battery algorithm delivery and support battery algorithm simulations to validate the battery algorithm and project the product KPIs. Requires battery modeling and algorithm knowledge and hands on experiences in data analysis and Matlab programing. Experience with Matlab is required, C++/python is a plus Experience with machine learning, optimization, and control algorithms is a plus Degree in DataScience/EE/CS/ChemE/MechE is preferred. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit ***************** At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $75 - $85 The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by appliable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at ***************. To report any concerns, please email us at *******************

Our optical sensing team develops optical sensors for next generation products. The team is seeking someone who has strong Python skills, a self-driven go-getter, with strong experience in optical instruments, data analysis and data visualization is required. Responsibilities: Manage and report the engineering build process using Python and JMP to analyze large sets of data and track key figures of merits. Validate the ambient light sensors' color and Liz sensing performance using Python and spectrometers. Assist with miscellaneous lab work to conduct failure analysis or research such as display light leakage, cover glass properties, affects from thermal environment, etc. Support in creating a performance simulation model using MATLAB. Lead end-to-end lab validation to support new optical sensor development. Develop and implement validation plan for hardware/software designs. Benchmark optical sensor performance from early prototype to product launch. Provide guidance and recommendation to production line testing requirements. Analyze data to draw conclusions and provide feedback to product design. Convert data to a visual plot and/or chart. Collaborate with cross-functional teams including Optical Engineering, Mechanical Engineering, Electrical Engineering and Process Engineering to deliver state-of-the-art sensing solutions. Deliver presentations of results in regular review with cross-functional teams. Requirements: Degree in Optics, Physics, Electrical Engineering or equivalent. B.S./M.S. and industry experience, or Ph.D. Strong background in optical measurements and data analysis. Experience in using Python or other coding languages for lab equipment control, data acquisition, and instrument automation. Need to be able to write/create, rewrite, revise customize and automate scripts. Hands-on experience with optical lab equipment (light sources, spectrometers, detectors, oscilloscopes, free space optics on optical bench, etc.). Excellent written and verbal communication skills. Solid teamwork and self-motivated for technical challenges. Preferred Skillset: Both Hardware and Software background Type: Contract (12+ months) Location: Cupertino, CA (100% onsite)

Midjourney is a research lab exploring new mediums to expand the imaginative powers of the human species. We are a small, self-funded team focused on design, human infrastructure, and AI. We have no investors, no big company controlling us, and no advertisers. We are 100% supported by our amazing community. Our tools are already used by millions of people to dream, to explore, and to create. But this is just the start. We think the story of the 2020s is about building the tools that will remake the world for the next century. We're making those tools, to expand what it means to be human. Core Responsibilities: Design and maintain data pipelines to consolidate information across multiple sources (subscription platforms, payment systems, infrastructure and usage monitoring, and financial systems) into a unified analytics environment Build and manage interactive dashboards and self-service BI tools that enable leadership to track key business metrics including revenue performance, infrastructure costs, customer retention, and operational efficiency Serve as technical owner of our financial planning platform (Pigment or similar), leading implementation and build-out of models, data connections, and workflows in partnership with Finance leadership to translate business requirements into functional system architecture Develop automated data quality checks and cleaning processes to ensure accuracy and consistency across financial and operational datasets Partner with Finance, Product and Operations teams to translate business questions into analytical frameworks, including cohort analysis, cost modeling, and performance trending Create and maintain documentation for data models, ETL processes, dashboard logic, and system workflows to ensure knowledge continuity Support strategic planning initiatives by building financial models, scenario analyses, and data-driven recommendations for resource allocation and growth investments Required Qualifications: 3-5+ years experience in data engineering, analytics engineering, or similar role with demonstrated ability to work with large-scale datasets Strong SQL skills and experience with modern data warehousing solutions (BigQuery, Snowflake, Redshift, etc.) Proficiency in at least one programming language (Python, R) for data manipulation and analysis Experience with BI/visualization tools (Looker, Tableau, Power BI, or similar) Hands-on experience administering enterprise financial systems (NetSuite, SAP, Oracle, or similar ERP platforms) Experience working with Stripe Billing or similar subscription management platforms, including data extraction and revenue reporting Ability to communicate technical concepts clearly to non-technical stakeholders

Citizenship Requirement: U.S. Citizens Only ITTConnect is seeking a Data Engineer / Analytics to work for one of our clients, a major Technology Consulting firm with headquarters in Europe. They are experts in tailored technology consulting and services to banks, investment firms and other Financial vertical clients. Job location: San Francisco Bay area or NY City. Work Model: Ability to come into the office as requested Seniority: 10+ years of total experience About the role: The Data Engineer / Analytics Specialist will support analytics, product insights, and AI initiatives. You will build robust data pipelines, integrate data sources, and enhance the organization's analytical foundations. Responsibilities: Build and operate Snowflake-based analytics environments. Develop ETL/ELT pipelines (DBT, Airflow, etc.). Integrate APIs, external data sources, and streaming inputs. Perform query optimization, basic data modeling, and analytics support. Enable downstream GenAI and analytics use cases. Requirements: 10+ years of overall technology experience 3+ years hands-on AWS experience required Strong SQL and Snowflake experience. Hands-on pipeline engineering with DBT, Airflow, or similar. Experience with API integrations and modern data architectures.

If you're hands on with modern data platforms, cloud tech, and big data tools and you like building solutions that are secure, repeatable, and fast, this role is for you. As a Senior Data Engineer, you will design, build, and maintain scalable data pipelines that transform raw information into actionable insights. The ideal candidate will have strong experience across modern data platforms, cloud environments, and big data technologies, with a focus on building secure, repeatable, and high-performing solutions. Responsibilities: Design, develop, and maintain secure, scalable data pipelines to ingest, transform, and deliver curated data into the Common Data Platform (CDP). Participate in Agile rituals and contribute to delivery within the Scaled Agile Framework (SAFe). Ensure quality and reliability of data products through automation, monitoring, and proactive issue resolution. Deploy alerting and auto-remediation for pipelines and data stores to maximize system availability. Apply a security first and automation-driven approach to all data engineering practices. Collaborate with cross-functional teams (data scientists, analysts, product managers, and business stakeholders) to align infrastructure with evolving data needs. Stay current on industry trends and emerging tools, recommending improvements to strengthen efficiency and scalability. Qualifications: Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent experience). At least 3 years of experience with Python and PySpark, including Jupyter notebooks and unit testing. At least 2 years of experience with Databricks, Collibra, and Starburst. Proven work with relational and NoSQL databases, including STAR and dimensional modeling approaches. Hands-on experience with modern data stacks: object stores (S3), Spark, Airflow, lakehouse architectures, and cloud warehouses (Snowflake, Redshift). Strong background in ETL and big data engineering (on-prem and cloud). Work within enterprise cloud platforms (CFS2, Cloud Foundational Services 2/EDS) for governance and compliance. Experience building end-to-end pipelines for structured, semi-structured, and unstructured data using Spark.

Experience Level: Mid-Senior (4+ years) About the Role This role supports the organization's data, analytics, and AI innovation efforts by building reliable data pipelines, developing machine learning solutions, and improving how information is collected, processed, and used across the business. This person is a collaborative problem-solver who can translate business needs into technical solutions, work confidently across large datasets, and deliver clear, actionable insights that help drive strategic outcomes. What They Do Support innovation projects by facilitating discussions, refining business processes, integrating data sources, and advising on best practices in analytics and AI. Build and maintain data architectures, APIs, and pipelines to support both operational systems and AI initiatives. Design and implement machine learning models, including developing prompts and AI-driven applications. Collaborate with technical and non-technical teams to improve data quality, reporting, and analytics across the organization. Manage large, complex datasets and develop tools to extract meaningful insights. Automate manual processes, optimize data delivery, and enhance internal infrastructure. Create dashboards and visualizations that clearly communicate insights to stakeholders. Apply statistical, computational, NLP, and ML techniques to solve business problems. Document processes, use version control best practices, and deploy models to production using enterprise platforms such as Azure. Ensure data security and privacy across systems, vendors, and applications. Experience & Skills 4+ years in a Data Engineering or DataOps/DevOps role. Strong experience with SQL, relational databases, cloud environments (Azure/AWS), and building/optimizing data pipelines. Ability to work with structured and unstructured data and perform root-cause analysis on data and integrations. Experience with AI/ML data preparation, preprocessing, feature engineering, and model deployment. Familiarity with vector databases, embeddings, and RAG-based applications. Strong communication skills and ability to collaborate across teams. Ability to handle confidential and sensitive information responsibly. Technologies Data & BI: SQL Server, T-SQL, SSIS/SSRS, ETL/ELT, Power BI, DAX, PowerQuery Programming: Python, R, C++, Julia, JavaScript, SQL File Formats: JSON, XML, SQL Extras (Nice to Have): PowerShell, Regex, VBA, documentation/process mapping, Tableau/Domo, Azure ML, legal tech platforms, LLM integration (OpenAI, Azure OpenAI, Claude), embedding models

We imagine a world where new medicines reach patients in months, not years, and where scientific breakthroughs happen at the speed of thought. Mithrl is building the world's first commercially available AI Co-Scientist. It is a discovery engine that transforms messy biological data into insights in minutes. Scientists ask questions in natural language, and Mithrl responds with analysis, novel targets, hypotheses, and patent-ready reports. No coding. No waiting. No bioinformatics bottlenecks. We are one of the fastest growing tech bio companies in the Bay Area with 12x year over year revenue growth. Our platform is used across three continents by leading biotechs and big pharmas. We power breakthroughs from early target discovery to mechanism-of-action. And we are just getting started. ABOUT THE ROLE We are hiring a Data Engineer, Knowledge Graphs to build the infrastructure that powers Mithrl's biological knowledge layer. You will partner closely with the Data Scientist, Knowledge Graphs to take curated knowledge sources and transform them into scalable, reliable, production ready systems that serve the entire platform. Your work includes building ETL pipelines for large biological datasets, designing schemas and storage models for graph structured data, and creating the API surfaces that allow ML engineers, application teams, and the AI Co-Scientist to query and use the knowledge graph efficiently. You will also own the reliability, performance, and versioning of knowledge graph infrastructure across releases. This role is the bridge between biological knowledge ingestion and the high performance engineering systems that use it. If you enjoy working on data modeling, schema design, graph storage, ETL, and scalable infrastructure, this is an opportunity to have deep impact on the intelligence layer of Mithrl. WHAT YOU WILL DO Build and maintain ETL pipelines for large public biological datasets and curated knowledge sources Design, implement, and evolve schemas and storage models for graph structured biological data Create efficient APIs and query surfaces that allow internal teams and AI systems to retrieve nodes, relationships, pathways, annotations, and graph analytics Partner closely with the Data Scientists to operationalize curated relationships, harmonized variable IDs, metadata standards, and ontology mappings Build data models that support multi tenant access, versioning, and reproducibility across releases Implement scalable storage and indexing strategies for high volume graph data Maintain data quality, validate data integrity, and build monitoring around ingestion and usage Work with ML engineers and application teams to ensure the knowledge graph infrastructure supports downstream reasoning, analysis, and discovery applications Support data warehousing, documentation, and API reliability Ensure performance, reliability, and uptime for knowledge graph services WHAT YOU BRING Required Qualifications Strong experience as a data engineer or backend engineer working with data intensive systems Experience building ETL or ELT pipelines for large structured or semi structured datasets Strong understanding of database design, schema modeling, and data architecture Experience with graph data models or willingness to learn graph storage concepts Proficiency in Python or similar languages for data engineering Experience designing and maintaining APIs for data access Understanding of versioning, provenance, validation, and reproducibility in data systems Experience with cloud infrastructure and modern data stack tools Strong communication skills and ability to work closely with scientific and engineering teams Nice to Have Experience with graph databases or graph query languages Experience with biological or chemical data sources Familiarity with ontologies, controlled vocabularies, and metadata standards Experience with data warehousing and analytical storage formats Previous work in a tech bio company or scientific platform environment WHAT YOU WILL LOVE AT MITHRL You will build the core infrastructure that makes the biological knowledge graph fast, reliable, and usable Team: Join a tight-knit, talent-dense team of engineers, scientists, and builders Culture: We value consistency, clarity, and hard work. We solve hard problems through focused daily execution Speed: We ship fast (2x/week) and improve continuously based on real user feedback Location: Beautiful SF office with a high-energy, in-person culture Benefits: Comprehensive PPO health coverage through Anthem (medical, dental, and vision) + 401(k) with top-tier plans

About us: Intuitive is an innovation-led engineering company delivering business outcomes for 100's of Enterprises globally. With the reputation of being a Tiger Team & a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers: Modernization & Migration Application & Database Modernization Platform Engineering (IaC/EaC, DevSecOps & SRE) Cloud Native Engineering, Migration to Cloud, VMware Exit FinOps Data & AI/ML Data (Cloud Native / DataBricks / Snowflake) Machine Learning, AI/GenAI Cybersecurity Infrastructure Security Application Security Data Security AI/Model Security SDx & Digital Workspace (M365, G-suite) SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility Email, Collaboration, Directory Services, Shared Files Services Intuitive Services: Professional and Advisory Services Elastic Engineering Services Managed Services Talent Acquisition & Platform Resell Services About the job: Title: Imaging Data Engineer/Architect Start Date: Immediate # of Positions: 1 Position Type: Contract/ Full-Time Location: San Francisco, CA Notes: Imaging data Engineer/architect who understands Radiology and Digital pathology, related clinical data and metadata. Hands-on experience on above technologies, and with good knowledge in the biomedical imaging, and data pipelines overall. About the Role We are seeking a highly skilled Imaging Data Engineer/Architect to join our San Francisco team as a Subject Matter Expert (SME) in radiology and digital pathology. This role will design and manage imaging data pipelines, ensuring seamless integration of clinical data and metadata to support advanced diagnostic and research applications. The ideal candidate will have deep expertise in medical imaging standards, cloud-based data architectures, and healthcare interoperability, contributing to innovative solutions that enhance patient outcomes. Responsibilities Design and implement scalable data architectures for radiology and digital pathology imaging data, including DICOM, HL7, and FHIR standards. Develop and optimize data pipelines to process and store large-scale imaging datasets (e.g., MRI, CT, histopathology slides) and associated metadata. Collaborate with clinical teams to understand radiology and pathology workflows, ensuring data solutions align with clinical needs. Ensure data integrity, security, and compliance with healthcare regulations (e.g., HIPAA, GDPR). Integrate imaging data with AI/ML models for diagnostic and predictive analytics, working closely with data scientists. Build and maintain metadata schemas to support data discoverability and interoperability across systems. Provide technical expertise to cross-functional teams, including product managers and software engineers, to drive imaging data strategy. Conduct performance tuning and optimization of imaging data storage and retrieval systems in cloud environments (e.g., AWS, Google Cloud, Azure). Document data architectures and processes, ensuring knowledge transfer to internal teams and external partners. Stay updated on emerging imaging technologies and standards, proposing innovative solutions to enhance data workflows. Qualifications Education: Bachelor's degree in computer science, Biomedical Engineering, or a related field (master's preferred). Experience: 5+ years in data engineering or architecture, with at least 3 years focused on medical imaging (radiology and/or digital pathology). Proven experience with DICOM, HL7, FHIR, and imaging metadata standards (e.g., SNOMED, LOINC). Hands-on experience with cloud platforms (AWS, Google Cloud, or Azure) for imaging data storage and processing. Technical Skills: Proficiency in programming languages (e.g., Python, Java, SQL) for data pipeline development. Expertise in ETL processes, data warehousing, and database management (e.g., Snowflake, BigQuery, PostgreSQL). Familiarity with AI/ML integration for imaging data analytics. Knowledge of containerization (e.g., Docker, Kubernetes) for deploying data solutions. Domain Knowledge: Deep understanding of radiology and digital pathology workflows, including PACS and LIS systems. Familiarity with clinical data integration and healthcare interoperability standards. Soft Skills: Strong analytical and problem-solving skills to address complex data challenges. Excellent communication skills to collaborate with clinical and technical stakeholders. Ability to work independently in a fast-paced environment, with a proactive approach to innovation. Certifications (preferred): AWS Certified Solutions Architect, Google Cloud Professional Data Engineer, or equivalent. Certifications in medical imaging (e.g., CIIP - Certified Imaging Informatics Professional).

You'll work closely with engineering, analytics, and product teams to ensure data is accurate, accessible, and efficiently processed across the organization. Key Responsibilities: Design, develop, and maintain scalable data pipelines and architectures. Collect, process, and transform data from multiple sources into structured, usable formats. Ensure data quality, reliability, and security across all systems. Work with data analysts and data scientists to optimize data models for analytics and machine learning. Implement ETL (Extract, Transform, Load) processes and automate workflows. Monitor and troubleshoot data infrastructure, ensuring minimal downtime and high performance. Collaborate with cross-functional teams to define data requirements and integrate new data sources. Maintain comprehensive documentation for data systems and processes. Requirements: Proven experience as a Data Engineer, ETL Developer, or similar role. Strong programming skills in Python, SQL, or Scala. Experience with data pipeline tools (Airflow, dbt, Luigi, etc.). Familiarity with big data technologies (Spark, Hadoop, Kafka, etc.). Hands-on experience with cloud data platforms (AWS, GCP, Azure, Snowflake, or Databricks). Understanding of data modeling, warehousing, and schema design. Solid knowledge of database systems (PostgreSQL, MySQL, NoSQL). Strong analytical and problem-solving skills.

Hybrid role 3X a week in office in Elk Grove, CA; no remote capabilities This is a direct hire opportunity. We're seeking a seasoned Senior Data Platform Engineer to design, build, and optimize scalable data solutions that power analytics, reporting, and AI/ML initiatives. This full‑time role is hands‑on, working with architects, analysts, and business stakeholders to ensure data systems are reliable, secure, and high‑performing. Responsibilites: Build and maintain robust data pipelines (structured, semi‑structured, unstructured). Implement ETL workflows with Spark, Delta Lake, and cloud‑native tools. Support big data platforms (Databricks, Snowflake, GCP) in production. Troubleshoot and optimize SQL queries, Spark jobs, and workloads. Ensure governance, security, and compliance across data systems. Integrate workflows into CI/CD pipelines with Git, Jenkins, Terraform. Collaborate cross‑functionally to translate business needs into technical solutions. Qualifications: 7+ years in data engineering with production pipeline experience. Expertise in Spark ecosystem, Databricks, Snowflake, GCP. Strong skills in PySpark, Python, SQL. Experience with RAG systems, semantic search, and LLM integration. Familiarity with Kafka, Pub/Sub, vector databases. Proven ability to optimize ETL jobs and troubleshoot production issues. Agile team experience and excellent communication skills. Certifications in Databricks, Snowflake, GCP, or Azure. Exposure to Airflow, BI tools (Power BI, Looker Studio).

, Inc. Stitch Fix (NASDAQ: SFIX) is the leading online personal styling service that helps people discover the styles they will love that fit perfectly so they always look - and feel - their best. Few things are more personal than getting dressed, but finding clothing that fits and looks great can be a challenge. Stitch Fix solves that problem. By pairing expert stylists with best-in-class AI and recommendation algorithms, the company leverages its assortment of exclusive and national brands to meet each client's individual tastes and needs, making it convenient for clients to express their personal style without having to spend hours in stores or sifting through endless choices online. Stitch Fix, which was founded in 2011, is headquartered in San Francisco. About the Team At Stitch Fix, our data science team combines data insights with expert human judgment to generate innovative recommendations that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members have autonomy to deliver impact through analyzing data, building reusable tools & processes and integrating with live engineering services. The diversity of the problems that we work on, and the data-rich environment of our business, make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems. We are looking for data scientists and leaders to join us as we revolutionize retail. The Logistics Algorithms team helps the business put the right things in the right places and at the right times in order to delight our clients and efficiently operate the business. Team members are owners of the health and efficiency of our fulfillment network, ensuring inventory availability for all clients so they can find the fits and styles they love. Alongside partnerships in merchandise planning, finance, and operations, we build tools to optimally manage the ingestion and circulation of merchandise and to power decision frameworks that help the business understand impacts through leveraging data insights in how inventory can work best to support the client journey. About the Role This role will combine technical expertise in data science with strong decision-making capabilities to drive data-informed strategic decisions across the organization. The ideal candidate will have a passion for solving complex business problems, utilizing data to derive insights, and providing actionable recommendations that guide key business decisions. As a Data Scientist at Stitch Fix, you will design, implement, and validate improvements to the way our inventory surfaces to clients, improving how we match our finite assortment of available inventory to our client demand. Optimizing our inventory has considerable opportunity for impact at Stitch Fix, by combining a deep focus on ensuring a client-right approach to inventory management with smart, active processes to increase business efficiency and unit margin. You're excited about this opportunity because you will… Build key relationships with stakeholders across product, engineering, finance, and operations and collaborate on translating business challenges into analytical questions that can be addressed using data science techniques Use decision-modeling frameworks, such as simulations, optimization models, and A/B testing, to assess potential outcomes and guide decision-making. Solution at high speed with a small, agile team of coworkers to produce outsized impact on the business Have the autonomy to identify unaddressed problems in the business as well as offer new, improved solutions to existing challenges Build tools and dashboards to support data-driven decision-making and empower non-technical stakeholders to leverage data insights in day-to-day decisions. Be exposed to a wide-open field of opportunity for impact with plenty of challenges to make your own Work in concert with and learn from a large, diverse, and world-class Algorithms team towards the common goal of transforming the way people find what they love. We're excited about you because… You have proficiency in Python You have experience with machine learning frameworks such as scikit-learn, statsmodels and other explainable predictive algorithms You're comfortable with SQL and experience working with large datasets to gather insights You have an understanding of statistical principles and how to apply them to data and experimental results, and can communicate derived insights to stakeholders to drive action You drive for resiliency. You take a principled approach to complexity, and can make smart bets on where to invest time and system burden for maximum business impact You're curious about what's happening outside your immediate sphere and how you can leverage insights elsewhere inside the domains you own You have familiarity with data visualization tools such as matplotlib, seaborn, looker etc You're happiest as a team player, able to balance time against multiple systems and work streams with defined objectives Why you'll love working at Stitch Fix... We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You'll bring these characteristics to life in everything you do at Stitch Fix. We cultivate a community of diverse perspectives- all voices are heard and valued. We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail. We win as a team, commit to our work, and celebrate grit together because we value strong relationships. We boldly create the future while keeping equity and sustainability at the center of all that we do. We are the owners of our work and are energized by solving problems through a growth mindset lens. We think broadly and creatively through every situation to create meaningful impact. We offer comprehensive compensation packages and inclusive health and wellness benefits. Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone's compensation-including a candidate's professional background, experience, location, and performance.This position is eligible for new hire and ongoing grants of restricted stock units depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. Salary Range$106,000-$177,000 USD This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data. Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here: **************************************************************** Recruiting Fraud Alert: To all candidates: your personal information and online safety are top of mind for us. At Stitch Fix, recruiters only direct candidates to apply through our official career pages at ************************************** or ************************************** Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers. If you are unsure if a message is from Stitch Fix, please email *********************. You can read more about Recruiting Scam Awareness on our FAQ page here: ***************************************************************************************