Top Data Science Jobs

Conduct research and predictive modeling for Citi Bike and shared mobility programs; build Power BI dashboards, reports, and briefing materials; translate complex data into actionable recommendations; monitor vendor compliance and data quality; document data procedures; maintain internal databases; and collaborate with Operations, Planning, Policy, leadership, and other stakeholders.

Develop member-level predictive models and longitudinal analyses for CMS Health Outcomes Survey measures and Medicare Advantage Star Ratings. Analyze survey drivers, trajectories, sampling, response rates, case-mix adjustments, and statistical significance. Build data pipelines and dashboards, validate methodologies, deploy models with engineering teams, and translate findings into clinical and operational interventions. Collaborate with Stars, clinical, care management, compliance, legal, and survey vendor stakeholders to ensure CMS-aligned outcomes and reporting.

Own and improve sales quota-setting models and methodologies using statistical modeling, forecasting, optimization, machine learning, and AI. Validate data, assumptions, model outputs, and business impact while partnering with Finance, Sales Compensation, Analytics, Engineering, and business stakeholders. Develop scalable analytical workflows and LLM solutions, including RAG applications, and communicate quantitative findings clearly to influence sales strategy, incentive programs, and operational decisions.

The Data Scientist will turn ambiguous B2B and go-to-market questions into actionable insights for strategy, monetization, product adoption, customer segmentation, field deployment, and organizational design. Responsibilities include analyzing product, customer, sales, revenue, and market data; partnering with cross-functional leaders; communicating recommendations to executives; applying AI tools; and helping establish the operating model for an emerging B2B data science team.

Build predictive failure models, real-time anomaly detection systems, diagnostic tools, and operational dashboards for spacecraft manufacturing, testing, and integration. Apply statistical modeling, causal inference, reliability analysis, and data mining to identify root causes, bottlenecks, quality issues, supplier risks, and process improvements. Develop reproducible Python and SQL analyses that support engineering decisions and mission reliability.

Build predictive models, anomaly detection systems, diagnostic tools, dashboards, and statistical quality-monitoring solutions for spacecraft manufacturing and testing. Analyze telemetry, production, supplier, and reliability data to identify failures, bottlenecks, delays, and root causes. Develop reproducible Python and SQL analyses and communicate actionable findings to engineering and operations stakeholders.

Build and maintain data science models and quantitative measurement frameworks to guide infrastructure decisions (chargers, parking, depots). Analyze infra efficiency and identify improvements. Collaborate cross-functionally with Supply Operations, Product, and Engineering to incorporate business context into model-driven decisions supporting expansion to new territories and cities.

Build data models, governed metrics, experiments, causal analyses, predictive models, and AI evaluation systems. Connect product and business data to measure enterprise customer value, develop internal AI tools, investigate metric changes, and provide strategic recommendations. The role partners with engineering, mentors analysts and data scientists, and supports analytics across product, sales, marketing, and finance in a hybrid environment.

Leads the global analytics strategy for Microsoft’s colocation capacity organization, owning executive metrics, OKR reporting, governance, forecasting, heatmaps, and decision-support products for a 480 MW capacity goal. Establishes trusted data frameworks, develops predictive and AI-assisted solutions, identifies portfolio risks, and drives cross-functional decisions. Provides technical leadership, mentors data professionals, and partners with senior leaders across capacity planning, engineering, deployment, finance, operations, and product teams.

Develops data science solutions by exploring, cleaning, analyzing, and visualizing structured and unstructured data. Builds predictive models, algorithms, machine learning techniques, and quantitative analyses to answer client questions and support informed decisions. Works with clients and leads complex solution development. Requires Secret clearance, a bachelor's degree, and travel up to 25%.

Product Data Scientists will embed with iOS or web teams to define product metrics, analyze user behavior, design experiments, build statistical and machine learning models, and turn findings into actionable recommendations. They will create dashboards, experiment readouts, decision memos, and AI-powered analytics workflows while partnering with Product, Design, Engineering, and Data Engineering.

Leads end-to-end research, development, validation, and maintenance of statistical and machine learning models for media measurement. Analyzes large datasets, translates findings into product insights, collaborates with engineering and product teams on scalable model deployment, and communicates results through visualizations and presentations. The role requires advanced statistical expertise, machine learning proficiency, Python, and independent project ownership.

Analyzes EHR, clinical, encounter, claims, and care-delivery data to develop clinical measures, cohorts, dashboards, KPIs, and actionable insights. Supports quality, access, preventive care, population health, outcomes, utilization, and care-gap analyses across multiple healthcare settings. Partners with clinicians, informatics, engineering, operations, and analytics teams while applying SQL, statistical programming, visualization, clinical data governance, and privacy practices.

Leads data science and analytics initiatives for Department of Warfare clients. Responsibilities include collecting, validating, normalizing, and analyzing complex data; developing predictive models and machine learning solutions; building BI applications, dashboards, and reports; improving automation; documenting data quality and analytical findings; and presenting recommendations to stakeholders and government leaders. The role also provides technical thought leadership and supports research and development in AI and machine learning.

Develop data-driven decision analyses for Department of Warfare clients. Responsibilities include collecting, validating, and analyzing data; creating predictive models, trend analyses, dashboards, and business intelligence solutions; documenting data quality and findings; developing data frameworks and pipelines; automating processes; and communicating insights to government stakeholders. The role requires knowledge of DoW acquisition, financial, and PPBE processes, along with an active Secret clearance and five or more years of experience.

Leads data science initiatives involving modeling, simulation, decision analysis, predictive modeling, data exploration, visualization, machine learning, and NLP. Develops algorithms and quantitative solutions, guides teammates, collaborates with clients, and translates complex data into actionable insights. Requires extensive experience with programming, data analysis software, and complex solution development, plus a TS/SCI clearance with polygraph.

Leads UCI schema analysis, integration, compliance, and lifecycle management for Air Force mission-level Command and Control systems. Designs interoperable data flows, improves data quality, supports testing and validation, documents system changes, and collaborates with technical and operational teams. The role also applies data analytics, machine learning, and statistical methods within secure defense environments.

Leads data science, AI, digital health, and analytics strategy for Immunology R&D. Partners with scientific, clinical, platform, and engineering teams to identify use cases, analyze workflows, evaluate emerging technologies, develop scalable solutions, and improve research execution and decision-making. The role focuses on healthcare, imaging, clinical, biomarker, real-world, and digital health data, including generative and agentic AI applications.

Conduct research on how consumer LLMs search, reason, and synthesize information; design experiments and causal inference analyses; support product and engineering decisions with rigorous measurement; and build data pipelines and recurring evaluations that turn evolving research findings into product capabilities.

Develop data science systems for motion imagery and full-motion video programs. Analyze aircraft operations and perform multi-object tracking on live video. Work with operational, archived, and live data in Elastic, Oracle, and Kafka; develop Python-based solutions and deploy code to Kubernetes using current GPU technologies. Subject matter expertise is welcomed, while the role supports mission-focused government capabilities.

Develops data science, AI, and machine learning solutions using structured and unstructured data. Responsibilities include data exploration, cleaning, analysis, visualization, predictive modeling, NLP, algorithm development, systems integration, and client advising. The role guides teammates, develops automated workflows and data products, and applies tools such as Python, R, SQL, distributed computing frameworks, and visualization platforms to solve complex public- and private-sector challenges.

Lead cross-functional analytics for MSN & Copilot Discover to drive engagement and revenue. Build forecasting, scenario-planning, and ML solutions, evaluate UX/monetization tradeoffs, inform product and monetization strategy, and communicate insights to senior stakeholders to influence investments and business outcomes.

Analyze multimodal healthcare, genomic, clinical, and biomedical imaging data to support drug discovery, biomarker development, disease progression modeling, clinical trial design, and real-world evidence analyses. The role involves building statistical and machine learning models, developing data pipeline modules and interactive tools, collaborating with clinical, genomics, and biology teams, contributing to data strategy, and communicating findings through publications and stakeholder presentations.

Build knowledge bases and extraction pipelines for generative AI/ML research. Develop metadata, annotation, provenance, and reproducible dataset workflows; analyze experimental, simulation, and evaluation data; create dashboards and reports; validate structured knowledge; and support research documentation and coordination with academic subcontractors.

Analyzes structured and unstructured datasets supporting U.S. Navy electronic warfare systems. Develops statistical, machine learning, NLP, data modeling, visualization, and reporting solutions to improve system readiness, reliability, maintainability, operational availability, and lifecycle performance. Integrates logistics, engineering, maintenance, and operational data; identifies trends and risks; and presents data-driven findings to technical and program stakeholders.