Data Scientist jobs at Pfizer - 397 jobs

A technical services support company is seeking Junior to Senior Level Data Scientists to join their team across various locations in the U.S. Candidates will develop analytics applications, apply machine learning, and visualize data findings. Required qualifications include education or extensive experience in relevant fields, along with security clearance. Comprehensive benefits package included. #J-18808-Ljbffr

To help keep everyone safe, we encourage all applicants to pay close attention to protect themselves during their job search. When applying for a position online you are at risk of being targeted by malicious actors looking for personal data. Please be aware we will only reach out via email using the domain quanata.com. Anything that does not match those domains should be ignored and considered a security risk. Job Summary We are looking for a Senior Data Scientist to be the strategic anchor for a functional team, translating ambiguous business challenges into powerful, end‑to‑end machine learning solutions and taking ownership of the data science lifecycle. Responsibilities Drive Full‑Cycle Solutions: spearhead high‑impact modeling projects from initial question to deployed solution, framing the problem, designing experiments, selecting evaluation criteria that connect to business value. Engineer the MLOps Backbone: build and own automated systems for model retraining, monitoring, and alerting; implement robust pipelines and CI/CD processes that ensure service stability. Elevate the Team: mentor junior data scientists, lead knowledge‑sharing sessions, and champion best practices to raise team standards. Influence Business Strategy: translate complex technical concepts into clear insights for non‑technical audiences, providing recommendations that directly shape functional priorities. Qualifications Relevant degree or equivalent experience, and 10‑12 years of data science work. Production‑grade proficiency in Python and SQL; mastery of multiple data science libraries and clean, scalable, well‑tested code. Proven track record of designing robust experimental frameworks and validation strategies. Business acumen - ability to turn vague challenges into well‑defined projects with clear success metrics. Mentorship mindset - natural teacher and collaborator who elevates others. Bonus Points Advanced credentials such as a PhD in a quantitative discipline or an actuarial designation (or progress toward one). Open‑source contributions - demonstrated track record of contributing to or maintaining widely used analytical libraries. Salary $250,000 to $400,000, depending on skills, experience, and internal salary structure. Our goal is a competitive and equitable compensation package. Benefits & Perks Health, dental, vision, life insurance and supplemental income plans. Headspace app subscription, monthly wellness allowance, and 401(k) with company match. Work‑from‑home equipment stipend of $2K for home office setup. Paid time off: four weeks PTO in first year; twelve weeks paid parental leave for new parents. Personal and professional development: up to $5,000 per year for learning, LinkedIn Learning subscriptions, Coaching via BetterUp. Location & Work Hours Remote‑first company; work from anywhere in the U.S. (excluding U.S. territories). Core meeting hours 9 AM - 2 PM Pacific time. Equal Employment Opportunity Statement Quanata, LLC is an equal‑opportunity workplace. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records. If you are a San Francisco resident, please read the City and County of San Francisco's Fair Chance Ordinance notice: *********************************************************************************************** This role is employed by Quanata, LLC, a separate company in the State Farm family of companies. If you require a reasonable accommodation, please reach out to your Talent Acquisition Partner for assistance. #J-18808-Ljbffr

A leading technology firm in San Francisco is seeking a Senior Data Scientist to be a key influencer in their team. The role involves taking ownership of the data science lifecycle and delivering powerful end-to-end ML solutions that drive impactful decisions for the business. The ideal candidate will have experience in translating business challenges into innovative data-driven strategies and making a quantifiable impact. This position allows for significant autonomy and the opportunity to work with cutting-edge technologies. #J-18808-Ljbffr

A cutting-edge cybersecurity firm in San Francisco is seeking a Data Engineer to design and architect their data infrastructure. In this high-impact position, you will be responsible for building scalable and secure database systems that operate across various environments. The ideal candidate should have over five years of experience in data engineering and a solid understanding of compliance frameworks. If you want to be at the forefront of autonomous cyber defense, this is your opportunity. #J-18808-Ljbffr

Who We Are Imprint is reimagining co-branded credit cards & financial products to be smarter, more rewarding, and truly brand-first. We partner with companies like Rakuten, Booking.com, H-E-B, Fetch, and Brooks Brothers to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. Our platform combines advanced payments infrastructure, intelligent underwriting, and seamless UX to help brands offer powerful financial products-without becoming a bank. Co-branded cards account for over $300 billion in U.S. annual spend-but most are still powered by legacy banks. Imprint is the modern alternative: flexible, tech-forward, and built for today's consumer. Backed by Kleiner Perkins, Thrive Capital, and Khosla Ventures, we're building a world-class team to redefine how people pay-and how brands grow. If you want to work fast, solve hard problems, and make a real impact, we'd love to meet you. The Team The Data Engineering team at Imprint is responsible for building and scaling the data infrastructure that supports product development, analytics, operations, and machine learning across the company. We own the pipelines, platforms, and processes that empower our stakeholders to trust and act on our data. The Role As our Staff Data Engineer, you'll architect our data platform while solving our most complex technical challenges. You'll build the foundation for Imprint's next decade of growth: scaling infrastructure for explosive expansion, delivering insights that drive million-dollar decisions, enabling bulletproof partner data sharing, and transforming how every team leverages data. Join us in creating a platform that doesn't just meet today's needs-but anticipates tomorrow's possibilities. What You'll Do Build & Scale Infrastructure Architect our next-generation data platform, optimizing Snowflake, dbt Cloud, and real-time CDC pipelines for enterprise scale Design secure, compliant partner data delivery systems via Snowflake shares, S3/SFTP integrations, and Marketplace listings Create mission-critical financial reporting pipelines with exceptional accuracy and reliability Drive Technical Excellence Establish company-wide data standards for modeling, lineage, contracts, and orchestration Champion data reliability, observability, and trust across all systems Make strategic technology decisions that balance innovation with pragmatism Lead & Mentor Elevate engineering practices across Analytics, Data, and Engineering teams Conduct architecture reviews and build reusable frameworks Share expertise through documentation, templates, and hands-on guidance What We Look For 10+ years of experience in data engineering or related fields, with proven experience owning platform-level architecture and strategy. Deep expertise in Snowflake, dbt Cloud, Change Data Capture frameworks, orchestration tools (Airflow, dbt Cloud), and reverse ETL. Strong background in external data sharing and partner integrations, including Snowflake data shares, S3/SFTP pipelines, and Marketplace listings. Proven ability to design and implement data governance and observability systems, including data contracts, lineage tracking, anomaly detection, and automated monitoring. Strong engineering skills in SQL and Python, emphasizing testing, CI/CD, and maintainability in complex data systems. Reputation as a mentor and technical authority who elevates the technical quality and rigor of peers and teams. Exceptional communication skills and the ability to influence technical and business leadership across multiple departments. Perks & Benefits Competitive compensation and equity packages Leading configured work computers of your choice Flexible paid time off Fully covered, high-quality healthcare, including fully covered dependent coverage Additional health coverage includes access to One Medical and the option to enroll in an FSA 16 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let's move the world forward, together. #J-18808-Ljbffr

A leading FinTech company in San Francisco is seeking a Staff Data Engineer to architect a next-generation data platform, optimize systems, and mentor teams. The ideal candidate has over 10 years of experience in data engineering, deep expertise in Snowflake and dbt Cloud, and strong skills in SQL and Python. Join us to shape the future of co-branded financial products while working in a dynamic, inclusive environment. #J-18808-Ljbffr

A cutting-edge data analytics firm in San Francisco is seeking a full-stack engineer to enhance user experiences and integrate AI tools within their platform. You will work on innovative projects that shape data interactions, collaborate with teams on product initiatives, and tackle UX challenges. Ideal candidates should possess 3+ years of software engineering experience, proficiency in React and Typescript, and a strong desire to work in AI development. This position offers a competitive salary and benefits, with a hybrid work model. #J-18808-Ljbffr

Data Scientist About the company: The mining industry has steadily become worse at finding new ore deposits, requiring >10X more capital to make discoveries compared to 30 years ago. The easy-to-find, near-surface deposits have largely been found, and the industry has chronically under-invested in new exploration technology, relying on the manual techniques of yesteryear - even as demand accelerates for copper, lithium, and other metals to build electric vehicles, renewable energy, and data centers. KoBold builds AI models for mineral exploration and deploys those models-alongside our novel sensors-to guide decisions on KoBold-owned-and-operated exploration programs. In the six years since founding, KoBold has become by far both the largest independent mineral exploration company and the largest exploration technology developer. Our data scientists and software engineers, who come from leading technology companies, jointly lead exploration programs with our renowned exploration geologists. KoBold has proven its first discovery with materially less capital than the industry average and found one of the best copper deposits ever discovered: the copper is far more concentrated than the global average of copper mines, and this asset alone is expected to generate meaningful revenue for decades. KoBold has a portfolio of more than 60 other projects, each of which has the potential for another high-quality discovery. KoBold is privately held; investors include institutional asset managers T. Rowe Price and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, and Standard Investments; and natural resources companies Equinor, BHP, and Mitsubishi. We are hiring a Data Scientist to help accelerate our mission. About the position In this role, you will build predictive models and apply a wide range of scientific computing, statistical, and physics-based methods to find places where there is evidence of ore-forming processes at work and to predict the locations of ore-grade mineralization in 2D and 3D. You will help build a worldwide dataset that underlies our exploration program, with careful attention to identifying and quantifying uncertainty in the data and in our predictions. You will create models and develop software to accelerate discovery of critical battery metals. You will join an outstanding team of data scientists and engineers and will work closely with KoBold's world-renowned geoscientists to incorporate our best understanding of the chemical and physical processes that create ore deposits. Working with your geoscience colleagues, you will create 2D and 3D geologic predictions, identify exploration targets, design field programs to collect data, and use that data to reduce the uncertainty in our predictions and guide the next phase of field work. Ultimately, your role is to help KoBold make valuable discoveries by building data tools to solve scientific problems. As one of the early members of this team, you will help build these tools from the ground up. Responsibilities The Data Scientist will: Help develop KoBold's proprietary software exploration tools. Find and curate geophysical, geochemical, geologic, and geographic data and integrate it into KoBold's proprietary data system. Build models to make statistically valid predictions about the locations of compositional anomalies within the Earth's crust. Create effective visualizations for evaluating model performance and enabling rapid interaction with the underlying data and key features. Develop and apply data processing, statistical, and physics-based techniques to geoscientific data - from computer vision to geophysical inversions - and use the results to guide our targeting efforts and inform our acquisition and exploration decisions. Present to and collaborate with our external partners and stakeholders. Qualifications A great Data Scientist candidate will have: Technical skills, including extensive experience with: Python's data science packages and general software engineering practices. Collaborative software development (git), and familiarity with software engineering best practices like unit test / integration test suites, and CICD pipelines. Cloud computing resources. Building predictive models, applying them to different problems, and evaluating and interpreting the results. Data from a variety of physical systems. Geospatial analyses and visualizations. Technical knowledge: Broad skills in and knowledge of applied statistics and Bayesian inference Substantial understanding of machine learning algorithms Work practices and motivation: Ability to design, scope and implement technical solutions to novel exploration problems Demonstrated ability to quickly absorb and synthesize complex information, with a track record of high intellectual rigor in a professional setting. Exceptional curiosity and eagerness to learn, with a proactive approach to exploring new concepts and technologies. Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities. Ability to independently prioritize multiple tasks effectively. It is also helpful but not required to have experience with: Creating machine learning models on geospatial data Geostatistics Image processing or computer vision Distributed computing applications for machine learning and other computations KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunities for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, marital status, disability, or veteran status. This position is full-time, exempt. Location: Location: KoBold is a remote first workplace, we are open to candidates currently residing anywhere in the United States or Canada. All candidates must be authorized to legally work in either the United States or Canada. Salary is one part of KoBold's total compensation. The US salary range for this role is between $125,000 and $235,000, and will depend on your skills, qualifications, experience, and location. In addition to salary, we offer equity compensation. We also offer benefits including medical, dental, and vision insurance, a 401k retirement plan, short & long term disability and life insurance. We also offer paid sick time and parental leave.

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. Essential Duties/Responsibilities: Adhere to our culture of humility, curiosity, and impact Process data using Python, PySpark, and Databricks Develop models and dashboards Learn the job while performing hands-on analytics and modeling Help business partners make more profitable decisions based on customer and prospect insights Working Conditions: Fully remote Minimum Requirements: 0-3 years of experience in data analysis or related field Master's degree in a quantitative discipline or equivalent practical experience Experience with statistical software and database languages Preferred Qualifications: Experience using data science to improve customer experience and business profitability PhD in a quantitative discipline Proficiency in Python packages such as PySpark, NumPy, pandas, scikit-learn, XGBoost, Matplotlib, and lifelines Theoretical and practical knowledge of methods such as frequentist statistics, Bayesian statistics, forecasting, optimization, causal inference, machine learning, and natural language processing Proficiency with version control Experience with reading and writing data in the cloud Ability to collaborate effectively with teammates across functions with strong skills in persuasive and informative speaking

The Opportunity As a Data Scientist at Otter.ai, you will be a key player within our Product Development organization. You will leverage your advanced data analytics skills and deep understanding of our products and market to drive strategic decision-making, optimize engagement and monetization strategies, and accelerate product adoption. Your work will significantly enhance customer experiences and contribute to our business success. If you are passionate about using data to drive business growth and want to be part of a team shaping the future of conversations, we invite you to apply and help us achieve our mission of making conversations more valuable. Your Impact * Collaborate with Product teams to understand business objectives and challenges, translating them into data-driven insights and recommendations. * Develop and implement predictive models, analytical tools, and methodologies to analyze product usage and customer behaviors. * Analyze large datasets to generate actionable insights that guide the development and optimization of engagement and monetization strategies. * Design and Execute experiments to test hypotheses and measure the effectiveness of various features, product experiences and strategies. * Partner with cross-functional teams, including Product Management and Engineering, to integrate data-driven insights into our products and services, driving continuous improvement and innovation. * Present findings and recommendations to key stakeholders, including executives, to inform strategic decision-making and shape the company's Product roadmaps. * Collaborate with Data Engineers to ensure data quality, accessibility, and reliability for analysis purposes. * Stay current with industry trends, emerging technologies, and best practices in data science, machine learning, and AI to drive innovation and competitiveness. We're Looking for Someone Who * 3+ years as a Data Scientist, in a software technology or AI-driven company. * Proficiency in SQL for querying large datasets, and expertise in Python and R for data manipulation, analysis, and visualization. * Strong background in data analysis, statistical modeling, and other data science techniques. * Familiarity with B2B SaaS business models. * Excellent ability to translate complex findings into actionable insights for non-technical stakeholders. * Proven ability to work effectively in cross-functional teams and manage multiple projects simultaneously. * Strong problem-solving skills and the ability to thrive in a fast-paced, dynamic start-up environment. About Otter.ai We are in the business of shaping the future of work. Our mission is to make conversations more valuable. With over 1B meetings transcribed, Otter.ai is the world's leading tool for meeting transcription, summarization, and collaboration. Using artificial intelligence, Otter generates real-time automated meeting notes, summaries, and other insights from in-person and virtual meetings - turning meetings into accessible, collaborative, and actionable data that can be shared across teams and organizations. The company is backed by early investors in Google, DeepMind, Zoom, and Tesla. Otter.ai is an equal opportunity employer. We proudly celebrate diversity and are committed to building an inclusive and accessible workplace. We provide reasonable accommodations for qualified applicants throughout the hiring process. Accessibility & Accommodations Otter.ai is committed to providing reasonable accommodations for candidates with disabilities in our hiring process. If you need assistance or an accommodation during any stage of the recruitment process, please contact *********** at least 3 business days before your interview. * Otter.ai does not accept unsolicited resumes from 3rd party recruitment agencies without a written agreement in place for permanent placements. Any resume or other candidate information submitted outside of established candidate submission guidelines (including through our website or via email to any Otter.ai employee) and without a written agreement otherwise will be deemed to be our sole property, and no fee will be paid should we hire the candidate. Salary range Salary Range: $155,000 to $185,000 USD per year. This salary range represents the low and high end of the estimated salary range for this position. The actual base salary offered for the role is dependent based on several factors. Our base salary is just one component of our comprehensive total rewards package. #LI-Hybrid

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time. Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience at scale. We've raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo. We're an in-office company, driven by a shared commitment to excellence and velocity. Our values- customers are everything , relentless momentum , winner's mindset , and stronger together -shape how we work and grow as a team. About the Role As a Data Scientist at Decagon, you'll bring deep technical rigor to how data is analyzed, tested, and applied across the business. You'll design and interpret experiments, apply advanced statistical methods, and build scalable analytical frameworks that directly inform product strategy and company performance. You'll work across Engineering and Product to establish robust measurement practices, expand the use of data-driven decision making, and uncover insights that shape Decagon's trajectory. This role blends strong analytical expertise with product acumen and the ability to influence at the highest levels. In this role, you will Conduct deep-dive analyses using advanced statistical methods on user behavior, product performance, and business outcomes to surface actionable insights. Enhance and extend Decagon's data models, metrics, and dashboards to ensure consistent, scalable reporting across teams. Design, implement, and analyze controlled A/B test experiments to measure product changes and customer experience. Collaborate with Product and Engineering to embed experimentation and measurement best practices into product development cycles. Build and continuously improve Decagon's data stack, ensuring scalable models, pipelines, and tools that empower self-serve analytics across the company. Communicate findings clearly and persuasively to executives and cross-functional stakeholders, influencing strategic decision-making. Evaluate and interpret the performance of ML models (e.g., classification, recommendation, LLM-based systems), helping the team reason through trade-offs, limitations, and business implications of model-driven decisions. Be the primary driver of experimentation culture at Decagon, helping define how we design, measure, and scale experiments across the business. What We're Looking For Strong ability to structure ambiguous problems, translate them into analytical approaches, and deliver business impact through data. Advanced proficiency in SQL and Python, with a solid foundation in statistics and experimental design. 5+ years (or equivalent experience) in data science or product analytics roles, ideally within high-scale consumer or marketplace products. Ability to reason about and analyze machine learning models, understanding their assumptions, trade-offs, and impact on product and customer outcomes. A proven track record of designing, running, and analyzing experiments at scale. Excellent communication skills, with experience influencing stakeholders and driving decisions across teams. Benefits Medical, dental, and vision benefits Take what you need vacation policy Daily lunches, dinners and snacks in the office to keep you at your best Compensation: $250k - $300k + equity

Profound is on a mission to help companies understand and control their AI presence. As a Data Scientist, you'll map every human-AI interaction to help brands turn AIs into their strongest advocates. You'll build predictive models, develop sampling techniques, and optimize brand visibility in AI-driven search (e.g., ChatGPT, Perplexity). Your work will directly impact how businesses shape their presence in the generative AI era. What You'll Do Develop and refine predictive models to analyze and forecast AI-driven search behavior. Design sampling and data classification techniques to improve AI-driven brand insights. Leverage LLMs/NLP to extract meaningful insights from unstructured text data. Work with large datasets, ensuring efficiency in querying, cleaning, and classification. Design and conduct A/B tests or other experimentation frameworks to measure impact. Collaborate with the founding team to turn complex data insights into actionable business strategies. Who You Are 3+ years of advanced analytics experience in technology, marketing, or advertising. Proficient in Python, R, and SQL, with hands-on experience querying and analyzing large datasets. Expertise in data sampling techniques, including stratified sampling, bootstrapping, and extrapolation. Strong background in predictive modeling and applying ML techniques to estimate event frequency. Deep understanding of Large Language Models (LLMs), their limitations, and real-world applications. Passionate about staying on top of AI research, especially in multi-modal AI and LLM advancements. Comfortable in a fast-moving, high-performance startup environment. This is an on-site role in our Union Square office-designed for builders who thrive on speed, iteration, and impact. We're happy to support visa sponsorship for qualified international candidates. For this role, the expected base salary range is $140,000 - $230,000. Profound's total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.

The Data Scientist will be responsible to create product reliability models and advanced analytics that drive strategic decisions about product improvements. This role will collaborate closely with cross-functional teams, including Engineering, Product Management, Quality, Services, and IT, to develop and deploy data-driven solutions that address complex customer challenges. You should understand the impacts of environmental and other field conditions as they relate to product reliability. In this role, you should be able to apply mathematical and statistical methods to predict future field performance by building product reliability models using software tools. PRINCIPAL DUTIES & RESPONSIBILITIES: * Analyze product reliability requirements * Create predictive models for field performance and product reliability * Assist in design of experiments and analysis to understand impacts of different design decisions and test results * Correlate predictive models with test results and field data REQUIREMENTS: * Bachelor's Degree in Math, Statistics, Data Science, Computer Science, Reliability Engineering, or equivalent experience * 1-5 years of experience * Basic knowledge in power/electrical engineering; AC and DC power * Basic knowledge in large- and small-scale cooling systems * LabVIEW, Python, or other coding and modeling language * Minitab or other statistical software tools * Power BI or other data visualization tools * Travel 15%

SRP is a Big Data startup company located in Princeton, New Jersey. Job DescriptionSRP is a big data startup company located in Princeton, NJ focused on Dynamic Pricing, run by seasoned alumni from Stanford University and Wharton. We are looking for a seasoned and highly experienced, hands-on big data architect. This person could potentially become a co-founder or CTO in this startup. Qualifications: * 10 to 15 years of experience in technology including Big Data and Hadoop * Experienced in Hadoop, Hive/Pig, various hadoop distributions such as Cloudera or Hortonworks * Experienced in Spark * Strong working knowledge with visualization tools such as Tableau or equivalent * Must have worked with really large data sets in the past * Experienced with databases, SQL, and AWS High energy and high enthusiasm are essential for this role, and a very strong drive to succeed. Learn more about us at: ****************** Additional Information This is a one time contracting project

Job Description Applied Physics is seeking a Data Scientist experienced with a diverse array of data types to join our dynamic and multidisciplinary team of independent and entrepreneurial computer scientists and engineers. In this role, you will collaborate with scientists and researchers in various areas, including data analysis, compression, text processing, graph analysis, machine learning, information visualization, as well as others. Responsibilities: Collaborate with scientists and researchers in various areas to develop state-of-the-art algorithms, software, and computer systems solutions to challenging problems. Assess the requirements for data science research from Applied Physics and the Advanced Propulsion Laboratory. Engage with other developers frequently to share relevant knowledge, opinions, and recommendations, working to fulfill deliverables as a team. Design technical solutions independently, participating as a member of a multidisciplinary team to analyze client requirements and designs, and implementing software and performing analyses to address these needs. Develop and integrate components for creating an operational information and knowledge discovery system. Requirements Bachelor's degree in computer science, computer engineering, or related field, or the equivalent combination of education and related experience. Comprehensive knowledge of one or more of the following: high-performance computing, scientific data analysis, statistical analysis, computer security, systems programming, and/or large-scale data management. Skilled in all phases of software development, including but not limited to feasibility requirements, design, implementation, integration, testing, and deployment. Experience developing software with C++, C, Java, Python, R, or Matlab, software applications in Linux, UNIX, Windows environments, data analysis algorithms, data management approaches, relational databases, or machine learning algorithms. Ability to successfully handle multiple time-sensitive projects across several disciplines. Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information. Benefits We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world. If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics. Applied Physics is an equal opportunity employer.

WARNING about fake job posting scams. There has been a recent wave of scams whereby third parties post fake job openings using a bogus email address that resembles ****************. Under the guise of asking you to fill out an application, the scammers are attempting to gather your personal information. See the Federal Trade Commission's warning on this topic at: ******************************************* The only official source for actual Biolinq job postings/openings is at ************************ While other job sites (such as LinkedIn, Indeed or Glassdoor) may pull from Biolinq's careers web page, you should visit *********************** to verify the accuracy of the openings found on third party web sites. About the Company Biolinq is a venture-backed digital health company developing a wearable biosensor platform that measures biomarkers important to the management of many clinical conditions including diabetes. This dynamic role is a part of a team of engineers and scientists developing a novel intradermal biosensor technology and the associated software data extraction and rendering SDK that will transform the way people manage their metabolic health. Job Purpose This is a dynamic role as part of a team of engineers and scientists developing a novel intradermal biosensor technology. This highly visible role within the Company will work with a cross-functional team of scientists and engineers and will be responsible for bench and clinical data analysis, algorithm development, and supporting planning, execution, and post clinical study activities. Duties and Responsibilities Algorithm development for Continuous Glucose Monitoring system and other analytes Develop signal processing algorithms for signal noise reduction and fault detection Analysis of data collected during the course of clinical trials to assess performance of Bioling sensors and help with root-cause analyses Implementing statistical analyses of data sets acquired in the clinical setting to assess safety, efficacy, and accuracy Processing large datasets using state of the art methods Assisting with preparation of reports or presentations to fulfil business or regulatory needs Other tasks as assigned Requirements Qualifications Master's degree and 8 years of experience required. PhD degree preferred. Scientific or Engineering discipline required. Minimum of 5 years' experience in signal processing, time series data analysis and algorithm development, preferably in a medical device setting Experience with advanced data analysis tools and methods; demonstrated understanding of statistics and statistical analysis of data Must be capable of supporting projects independently without supervision Experience with advanced computing languages such as Python, R, or Matlab Experience with machine learning and data mining methods Ability to interface with both clinicians and R&D team and work in a fast-paced, multi-disciplinary environment Capacity to manage multiple projects and communicate ideas clearly to the team; excellent written and verbal communication skills Working Conditions General office and laboratory. Physical Requirements While performing the duties of this job, the employee is regularly required to stand; walk; sit; use hands to handle or feel; reach with hands and arms; climb or balance; stoop, kneel, crouch, see, talk or hear in a standard office environment. Employee may occasionally lift/or move up to 15 pounds. BENEFITS Medical, dental, vision, health savings account, flexible spending account, life and long-term disability insurance, 401(k) plan, holidays, and PTO. At Biolinq we fully subscribe to the principles of Equal Employment Opportunity. It is our policy to provide employment, compensation, and other benefits related to employment based on qualifications, without regard to race, color, religion, national origin, age, sex, veteran status, genetic information, disability, or any other basis prohibited by federal, state or local law. In accordance with requirements of the Americans with Disabilities Act and applicable federal, state and/or local laws, it is our policy to provide reasonable accommodation upon request during the application process to applicants in order that they may be given a full and fair opportunity to be considered for employment. As an Equal Opportunity Employer, we intend to comply fully with applicable federal, state and/or local employment laws and the information requested on this application will only be used for purposes consistent with those laws. To the extent required by applicable law, The Company maintains a smoke- free workplace. As part of our efforts to ensure fair and equal pay based on merit, Biolinq supports pay transparency internally and during the recruitment process. The U.S. base salary range reasonably expected to be paid for this role is: $150,000 to $180,000 per year. We may ultimately pay more or less than the posted range. Actual compensation packages are commensurate with experience and based on a variety of factors that are unique to each candidate including, but not limited to: skill set, depth of experience, education, certifications, and specific work location. The range displayed reflects the minimum and maximum target for new hire salaries for the job across the U.S. The total compensation package for this position may also include an annual performance bonus and/or other applicable incentive compensation plans. Biolinq also offers a comprehensive package of benefits including paid time off (vacation, holidays, sick time, parental leave), medical/dental/vision insurance, and 401(k) to eligible employees, subject to the terms and conditions of the applicable plans and any written agreement between the parties. Your recruiter can share more about the total compensation package during the hiring process. Please note: The information contained herein is not intended to be an all-inclusive list of duties and responsibilities of the job, nor are they intended to be an all-inclusive list of the skills and abilities required to do the job. Management may, at its discretion, assign or reassign duties and responsibilities to this job at any time. The duties and responsibilities in this job description may be subject to change at any time due to reasonable accommodation or other reasons. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions. An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability. If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact Biolinq Talent Acquisition at ******************* Salary Description $150,000-$180,000

Join MonoSol's forward thinking Quality team and turn raw manufacturing data into actionable insights that raise product quality and process efficiency. You'll sit at the intersection of data science and manufacturing engineering to mine and utilize high-frequency production data for building predictive models and guiding teams on the levers that control critical quality attributes. You'll be an internal expert who bridges advanced data science with practical plant operations and a critical member to drive digital transformation across the company. Responsibilities * Leadership and Direction * Champion best practices in data governance, reproducibility, and experiment design; contribute to MonoSol's growing analytics community. * Data Engineering * Connect to historians/MES (manufacturing execution software), write efficient data pipelines to profile large time-series and batch datasets to discover key factors driving manufacturing defects and variability. * Predictive Modeling & Analytics * Train, test, and maintain regression/classification models (e.g. linear regression, XGBoost, TensorFlow). Emphasize and effectively communicate model outputs to key stakeholders. * Performance Improvement through ML * Integrate predictive models with real-time dashboards or control-room alerts that have a positive financial impact * Efficient Reporting with Visualization & Storytelling * Build clear dashboards (e.g. Power BI, Spotfire, or Custom) and present findings to production, maintenance, and leadership teams * Model Deployment & Monitoring * Package models for deployment in production environments using either cloud-based or on-premises infrastructure as needed. Set up dashboards and alerts to provide near-real-time insights and leading indicators for operators and engineers. * Data and Analytics Strategy * Make recommendations to improve data and analytics systems and platforms, contributing to the continuous improvement and refinement of data and analytics strategy at MonoSol. * Data Architecture * Help define data standards (naming, sampling, governance) for projects. * Continuous Improvement & Collaboration * Partner across manufacturing teams to translate model outputs into actions; coach colleagues on data-driven methods. Translate model findings into root-cause actions. * Personal Development * Stay current on manufacturing analytics, MLOps, and Six Sigma best practices; pursue certifications or conferences as needed. Typical Tasks * Extract, clean, and feature-engineer high-velocity plant data from manufacturing systems. * Design and extract meaningful features from time-series, batch, and categorical data to improve model performance and interpretability. * Build and evaluate predictive models (regularized linear regression, gaussian process regression, gradient boosting, neural networks); create simulation notebooks for process scenarios. * Deploy models in production environments (cloud or on-premises) using APIs or integrated systems; monitor performance for drift and retrain as needed to maintain accuracy. * Perform root cause analysis using data-driven techniques to identify sources of defects or process inefficiencies * Create intuitive dashboards that link inputs to predicted quality metrics. * Work closely with quality engineers, process engineers, and production teams to define the problem, validate model results, and co-develop solutions that are both technically sound and operationally practical. * Document methodologies, models, and findings in a clear and reproducible manner. * Present insights to operators, engineers, and executives Qualifications * Education * Bachelor's degree in chemical engineering, Mechanical Engineering, Data Science, Statistics, Computer Science, or related field (required). * Master's or graduate certificate in Data Science, Analytics, or related field (preferred). * Experience * 3+ years of statistical modeling, applied machine learning, data science, or advanced analytics preferably in process control and manufacturing. * Proven success in improving yield, uptime, or quality with statistical or ML models. * Familiarity with statistical process control (SPC), control charts, and quality metrics. * Six Sigma green belt or higher (preferred) * Technical Skills * Proficiency in Python or R for data analysis and modeling. (e.g., pandas/scikit-learn or dplyr/caret/tidymodels). * Experience with deep learning frameworks (e.g. TensorFlow, py Torch) * Strong SQL skills and working with relational databases; experience with cloud platforms (AWS SageMaker, Azure ML) is a plus. * Soft Skills * Ability to clearly communicate and translate model outputs into actionable recommendations for manufacturing-floor teams, engineering staff, and executive leadership. * Comfortable working in cross-functional settings and driving change Applicable only to applicants applying to a position in any location with a pay disclosure requirements under state or local law: The compensation range that is described below is the possible base pay compensation that the company believes in good faith that it will pay for this role at the time of posting based on job grade for the position. Individual compensation within this range is based on many factors such as years of experience etc. so the company might pay more or less than the posted range and it is understood that this range may be modified in the future. In addition to base compensation, MonoSol provides a yearly incentive compensation bonus, a profit sharing bonus when eligible, a comprehensive benefits package including medical, dental, vision insurances, short term disability, long term disability, accidental death and dismemberment, term life insurance, voluntary term life insurance, transit flexible spending account (if applicable), employee assistance program, identity theft protection, 401k and paid time off (vacation and sick days). Compensation range - $86,907.87 - $146,142.27 Incentive Compensation Bonus Target - 10% Paid time off amount - 15 days Closing The above statements are intended to describe the general nature and level of the work being performed by employees assigned to this position. This is not intended as an exhaustive list of all responsibilities, duties, and skills required. MonoSol, LLC reserves the right to make changes to the job description whenever necessary. Disclaimer As part of MonoSol, LLC's employment process, finalist candidates will be required to complete a drug / alcohol test, physical, and background check prior to employment commencing. MonoSol, LLC is an equal opportunity employer. All qualified applicants will be considered without regard to race, national origin, gender, age, disability, sexual orientation, veteran status, or marital status.

At Young Innovations, we foster a dynamic environment where team members make an impact every day as part of a collaborative, inclusive culture. Together, we serve the dental profession and their patients, united in our mission of achieving a Lifetime of Oral Health™ We embrace diverse perspectives and encourage bold thinking, challenging traditional approaches with a bias for action. Whether you're looking to expand your skills or grow your career, Young is here to support your goals and continuous learning. At Young, YOU are at the core of what we do. Position Overview: The Data Scientist will drive adoption and implementation of artificial intelligence, machine learning, and strategic analytics within our global data Fabric environment. This Data Scientist is ideal for someone with a strong foundation in statistical analysis, machine learning, and natural language processing, particularly in the application and fine-tuning of Large Language Models (LLMs). This professional will bring expertise in correlation analysis, predictive modeling, and the ability to work with large, complex datasets to drive data-driven decision-making across the organization. You'll like this role if: You like building processes from the ground up Partnering across the business Wearing multiple hats in a face paced environment Why You'll Love Working Here: Medium sized company - not too big, not too small - just enough to get things done and see your impact. Did we say benefits? Full medical, dental, vision, 401k, parental leave, paid holidays, paid time off, and more! You will have the ability to create everything from the ground up and fully own this function. Who you'll work with: Stakeholders from all across the business - IT, Supply Chain, Finance, Marketing, and more. What You'll Do: AI/ML Development & Integration Integrate large language models (LLMs)-such as OpenAI, BERT, and LLaMA-into business processes and products to enable text summarization, classification, personalized recommendations, and conversational interfaces. Build and optimize predictive models using advanced machine learning techniques to support forecasting, customer segmentation, retention strategies, fraud detection, and other high-impact business functions. Stay up to date with advancements in AI/ML, NLP, and data analytics; proactively recommend new tools, frameworks, and best practices to enhance capabilities. Statistical & Analytical Modeling Perform statistical analyses to uncover correlations and causal relationships across structured and unstructured data, identifying key drivers of business performance and emerging trends. Develop customer segmentation frameworks by analyzing behavioral, transactional, and demographic data to support personalized marketing and engagement initiatives. Translate complex results into clear, actionable insights through dashboards, visualizations, and reports for both technical and non-technical audiences. Leverage large-scale datasets (e.g., customer interactions, transaction records) using distributed computing and modern data platforms to support data-driven decision-making. Cross Functional & Strategic Collaboration Partner with Product, Marketing, Commercial, Customer Service, Finance, and Operations teams to understand analytical needs and deliver impactful solutions. Support enterprise-wide initiatives, including M&A data integration and other strategic analytics projects. Qualifications What You'll Bring: Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Masters, MBA and/or PhD a plus 3+ years of professional experience in data science, analytics, or machine learning roles Hands-on experience working with and implementing Large Language Models (LLMs) and NLP techniques Experience working in a private equity is a plus Technical Skills Strong foundation in statistical analysis and predictive modeling, including correlation analysis, hypothesis testing, regression, classifications, and time-series forecasting using tools like Phython (SciPy, statsmodels), R, or SaaS Experience working with large datasets and data warehouses using SQL and cloud platforms (i.e. AWS, GCP, Azure) Strong proficiency in Python and experience with ML frameworks (ie. PyTorch, TensorFlow) The pay range reflects the minimum and maximum target for the position at the time of posting. Within the range, the compensation will be determined based on education/training, skill set, experience, and other organizational needs. Physical Requirements/Working Locations: Office/Remote Environment This position is based in an office environment and is primarily sedentary in nature. It requires regular use of standard office equipment, including computers, phones, photocopiers, scanners, filing cabinets, and fax machines. Some roles may involve wearing a headset and sustained computer use for 8 or more hours per day. Employees may be required to sit, stand, or walk for extended periods, and occasional bending, lifting, or carrying items up to 50 pounds may be necessary. We are an Equal Opportunity Employer and value diversity at all levels of the organization. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world's energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones. To learn more about us, please visit: ********** What We Offer: A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company. The opportunity to contribute directly to a meaningful scientific project-accelerating the global energy transition-with a clear and broad public impact. Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology. Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering. Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions. What we Need: The SES AI Prometheus team is seeking an exceptional Data & Evaluation Applied AI Scientist to serve as the domain expert ensuring that SES AI's complex battery-domain knowledge is correctly represented and validated within advanced AI systems, including LLM pipelines and multi-agent workflows. This role is vital for bridging the gap between raw battery materials knowledge and structured, AI-trainable data. As the Data & Model Quality Manager, you will focus on the integrity, structure, and fidelity of the knowledge embedded within our AI systems. Essential Duties and Responsibilities: Data Curation & Validation Translate deep Battery Materials Knowledge and next-generation battery concepts into correctly structured, high-quality, AI-trainable data. Lead processes for rigorous data validation, cleaning, and annotation to ensure consistency and correctness across all datasets. Oversee the creation and management of benchmark datasets and design domain-specific multimodal evaluations to test model accuracy. AI System Quality & Correctness Partner closely with AI architecture and engineering teams to ensure the correctness, reliability, and scientific reasoning quality of models, including LLM creation and multi-agent orchestration. Implement techniques, including those inspired by reinforcement learning (RLHF), to tune and validate model behavior against established scientific principles. Ensure that resulting models accurately understand molecular chemistry, materials data, and complex scientific reasoning in the battery domain. Strategy & Collaboration Drive the application of Battery Informatics principles across all data pipelines and modeling effots. Education and/or Experience: Education: Ph.D. in Chemical Engineering with a focus on Lithium battery systems, Materials Science, or a closely related computational/domain field. Domain Expertise: Deep expertise in battery materials, particularly knowledge required to convert complex, real-world data into AI-trainable formats. Data Quality & Validation: Proven experience in data validation, annotation, and benchmark creation for complex scientific or engineering datasets. AI Exposure: Experience working with advanced AI systems, including familiarity with LLM pipelines and the principles of multi-agent orchestration. Applicable Background: Experience in roles such as Applied Scientist in Molecular/Materials AI or similar specialist roles focused on AI system quality in a scientific domain. Preferred Qualifications: Advanced AI Techniques: Experience with specialized techniques used for model tuning and alignment, such as Reinforcement Learning from Human Feedback (RLHF). Industry Precedent: Previous experience in specialized environments like battery focus labs, materials data science groups, or AI4Science teams with a focus on agent pipeline building and model tuning (e.g., drawing from precedents like DeepMind or Fair Labs). Evaluation Design: Direct experience designing and executing domain-specific multimodal evaluations for complex AI models. Computational Focus: Experience as a Computational battery AI specialist.