Top Data Science Jobs

Develop and deploy predictive and generative AI models for personalization, forecasting, marketing automation, conversational agents, and other business applications. Perform exploratory analysis, statistical modeling, causal inference, and A/B testing. Build Python-based modeling workflows, collaborate on productionization and MLOps, develop RAG and agentic systems, and communicate insights to technical and non-technical stakeholders across the organization.

Performs exploratory, descriptive, diagnostic, and predictive analysis supporting Navy Reserve readiness and mission assurance. Develops data models, dashboards, visualizations, and AI/ML solutions; analyzes data quality and anomalies; and supports automated monitoring and governance. Collaborates with engineers, architects, analysts, and government stakeholders to validate data, identify trends, gather requirements, and recommend solutions. Communicates findings through analytical products and decision-support tools.

Develop, deploy, and monitor fraud detection models and pattern-recognition pipelines using Python, SQL, machine learning, and large transactional datasets. Partner with Fraud Operations to refine models, reduce false positives and negatives, analyze emerging fraud trends, and improve underwriting and verification strategies. Communicate insights to senior stakeholders, apply AI in production, and lead team members and initiatives.

Analyzes complex clinical, biological, genetic, and imaging datasets supporting macular degeneration research. Builds basic statistical, predictive, and machine learning models; validates data; develops imaging algorithms; creates visualizations; interprets research protocols; resolves analytics issues; and supports publications. Uses programming and statistical tools to transform data, answer research questions, improve workflows, and communicate findings to investigators and analytics teams.

Develop and deploy machine learning, statistical modeling, and advanced analytics solutions for audit, risk management, cybersecurity, and fraud detection. Manage data science projects from development through implementation, deliver actionable insights, mentor junior data scientists, and help shape the team’s strategic direction while addressing complex data challenges.

Leads technical work in climate data science, transforming atmospheric, oceanographic, environmental, earth observation, geospatial, and time-series datasets into actionable tools and insights. Partners with communities, policymakers, businesses, researchers, and cross-sector organizations; develops climate risk models and related analyses; translates complex science for nontechnical audiences; and leads collaborative projects, researchers, and data teams.

Leads data science, advanced analytics, dashboard development, data visualization, process automation, and metric governance for technology and enterprise operations risk. Develops descriptive, diagnostic, and predictive reporting; validates data quality, KRIs, KPIs, controls, and models; partners with stakeholders to deliver actionable insights. Uses SQL, Python, Power BI, Copilot tools, and Power Automate to improve reporting and operational efficiency while maintaining regulatory and internal control standards.

Leads advanced analytics, data visualization, dashboard development, reporting, metric governance, data quality, and process automation for technology and enterprise risk management. Uses SQL, Python, Power BI, Copilot, and Power Automate to create actionable insights, validate KRIs and KPIs, automate reporting, and improve operational efficiency. Partners with stakeholders, supports self-service BI adoption, maintains internal controls, and escalates risk-related issues. The role also requires dashboard standards, data modeling, visualization storytelling, and limited people leadership.

Develop product analytics and experimentation for Spotify’s Discovery Mode promotion tools. Build metrics, instrumentation, dashboards, and actionable insights to improve customer engagement and business outcomes. Collaborate with product, engineering, research, design, marketing, and other data science teams to identify opportunities, test hypotheses, and influence product decisions through clear data storytelling.

Design, develop, deploy, and monitor advanced deep learning models for fraud detection, risk management, and identity verification. Lead machine learning initiatives, research novel algorithms, manage end-to-end model lifecycles, collaborate with Product, Engineering, and Risk teams, and communicate insights to technical and executive stakeholders. Mentor data scientists and drive high-impact delivery, data quality, experimentation, and continuous improvement.

The Senior Data Scientist will analyze product, customer, and risk data to improve Support and Risk Operations. Responsibilities include defining metrics, forecasting demand, modeling staffing and queue health, evaluating experiments and policies, monitoring risk models for bias and drift, and communicating decisions to product, engineering, and risk stakeholders. The role also leads technical standards, develops reusable analytical tooling, mentors data scientists, and uses AI tools and agent workflows to improve analytical quality and efficiency.

Lead data science initiatives for Risk and Support Operations by analyzing customer and product data, defining metrics, forecasting demand, evaluating experiments and risk policies, and building decision frameworks. Use AI tools and agent workflows to improve analytical efficiency. Partner with product, engineering, and risk teams, communicate insights to senior stakeholders, establish technical standards, mentor data scientists, and support hiring.

Leads the design and production deployment of scalable data science and machine learning systems for aircraft, manufacturing, and operations data. Analyzes high-frequency sensor data, develops predictive models, builds Python tools and pipelines, establishes MLOps and engineering standards, and mentors data scientists. Partners with engineering teams and executives to translate complex analyses into strategic decisions related to aircraft safety, reliability, and performance.

Design and deploy optimization and machine learning models for allocating scarce parts and resources across competing programs. Responsibilities include formulating MILP and constraint optimization models, forecasting demand and supply risk, building data pipelines, validating outputs, communicating tradeoffs to stakeholders, mentoring junior data scientists, and partnering with software engineers to productionize scalable services.

Performs quantitative analysis, data integration, exploratory analysis, visualization, and machine learning to uncover insights from complex datasets supporting intelligence community missions. Uses Python and SQL to process data, develop predictive models, and communicate findings to technical and nontechnical stakeholders. Requires a TS/SCI clearance and bachelor's degree, with preferred experience in Spark, JEMA, web development, cloud services, ETL, geospatial data, and dashboards.

Own end-to-end data science for growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate insights; and drive recommendations and decisions with cross-functional stakeholders. The role requires independent analytical problem-solving, strong SQL or Python skills, persuasive communication, and ownership of ambiguous problems with measurable business impact.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and drive data-informed decisions with cross-functional stakeholders. The role requires independently structuring data, solving ambiguous problems, communicating recommendations clearly, and delivering measurable business impact.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface insights; and drive data-informed decisions with cross-functional stakeholders. The role requires independent analytical problem-solving, SQL or Python proficiency, strong communication, and ownership of ambiguous initiatives through measurable business impact.

Own end-to-end data science for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, analyses, experiments, reports, and recommendations. Translate complex findings into clear decisions, influence leadership, and drive measurable outcomes. Work independently with SQL or Python in a hands-on, remote-first environment.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and drive data-informed decisions with cross-functional stakeholders. The role requires independent data work, strong analytical reasoning, persuasive communication, and ownership of ambiguous problems through measurable business impact.

Own end-to-end data science for growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence stakeholders and leadership decisions. The role requires independent data work, strong analytical thinking, persuasive communication, and ownership of ambiguous problems through measurable outcomes.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and drive data-informed decisions and outcomes. The role requires independently structuring and interpreting data, communicating findings to leadership, and solving ambiguous problems using SQL or Python.

Own end-to-end data science for growth, product, AI, automation, or partnerships. Define business problems, metrics, reports, analyses, and experiments; communicate insights and recommendations; and drive decisions and measurable outcomes with cross-functional stakeholders. The role requires independent analytical problem-solving, strong SQL or Python skills, persuasive communication, and ownership of ambiguous initiatives.

Develop predictive models and automated analytic solutions using structured and unstructured data. Responsibilities include collecting, cleaning, validating, and analyzing large datasets; building ETL pipelines; evaluating machine learning models; communicating findings to technical and non-technical stakeholders; mentoring users; and supporting mission-critical US PACOM analytics with an active Secret clearance.

Supports the analysis of complex data for National Reconnaissance Office mission efforts. Designs and integrates large datasets, evaluates data quality, prepares data for predictive modeling, and applies AI, machine learning, and statistical methods. The role also supports platform testing, quality assurance, process automation, technical documentation, data compliance, and ethical technology use while advising leadership on mission impact and data-informed decisions.