Top Data Science Jobs

Seeking a Senior Data Scientist to provide technical expertise for a U.S. Government customer, focusing on data analytics and signals analysis.

The Principal Data Scientist will lead the design of knowledge graph infrastructure in Immunology, standardizing and integrating extensive biomedical data for cross-functional analytics and insights. Responsibilities include data modeling, ontology curation, and collaborating with various scientific teams.

Build and maintain large commercial datasets and predictive/forecasting models (BigQuery, dbt, SQL, Python). Design causal and experimental analyses to measure promotion impact and price elasticity. Partner with commercial, finance, and executive stakeholders to inform pricing, distribution, and investment. Deploy LLMs and AI agents to classify unstructured data and build tools that democratize data access.

Embedded on a core business team, own analytics end-to-end: define problems, design metrics and experiments, pull and analyze data, build reports, surface insights, and drive measurable outcomes by recommending and influencing product, growth, and operations decisions.

Embed within a core business area to define problems, build metrics, run analyses and experiments, create reports, and drive data-driven recommendations to improve product, growth, AI/automation, or partnerships outcomes.

Lead technical data science efforts for VA clinical and operational analytics: build and validate ML models, integrate EHR/CDW data, ensure VA governance compliance, produce dashboards and visualizations, and support Agile delivery to translate insights into operational improvements.

Lead data science efforts for the Program Management Office: optimize and secure SQL databases, build and manage ETL pipelines, create BI dashboards in Tableau/Power BI, automate processes with Python and Airflow, use GitLab in Agile workflows, and perform statistical analysis and data mining to surface trends and insights.

As a Senior Data Scientist, you will design and deploy machine learning and graph algorithms to enhance identity trust solutions, own end-to-end projects, and collaborate with product and engineering teams to improve KYC and compliance products.

Lead development of mission-ready data exploitation and geospatial analytics solutions using Python. Integrate web APIs, build dashboards and visualizations, query relational databases, use GIS tools, and produce technical documentation. Operate independently at senior level, guide junior staff, collaborate across Intelligence Community analysts, and advise government leadership.

Analyze internal and external datasets to identify macro demand indicators, incorporate macro signals into forecasting, guide forecast biasing, interpret ML outputs, and deliver actionable market insights to planning, FP&A, and leadership.

Perform statistical and operational analyses, assess and improve data quality, use SQL and GIS/geospatial data to support reporting, evaluate program outcomes, build public-facing reporting tools, and coordinate data sharing and communications with stakeholders.

The Senior Data Scientist will lead data analytics projects, interface with clients, and develop predictive models for business intelligence using various data tools.

As a Senior Data Scientist, you'll design data-driven solutions, analyze performance, collaborate across teams, and communicate insights to drive decision-making.

Lead risk-focused data science work by analyzing transactions and user behavior, developing automated risk controls and decisioning systems, advising leadership on risk strategy, and partnering cross-functionally to improve risk processes and scalability in a fast-paced fintech environment.

As a Lead Data Scientist, you will lead a team to develop AI solutions, collaborate with cross-functional teams, design predictive models, and ensure data quality in machine learning pipelines.

The Lead Data Scientist will oversee end-to-end data science projects, develop statistical models and machine learning algorithms, and collaborate across teams to deliver impactful data solutions.

Lead causal inference and marketing mix modeling to measure and optimize marketing investments. Define problems with stakeholders, build statistical pipelines and production models, design and analyze experiments, deploy solutions, and support automated campaigns via science on-call rotation to drive Growth outcomes.

Lead causal inference and marketing mix modeling to measure and optimize marketing investments. Drive end-to-end data science work for Growth: define problems with stakeholders, build statistical pipelines, write production code, design and analyze experiments, deploy production models, and participate in on-call rotations to ensure automated campaigns run smoothly.

Lead measurement and optimization of marketing investments using causal inference and MMM. Deliver end-to-end data science solutions for Growth: define problems, build statistical pipelines, productionize models, design and analyze experiments, own roadmaps, and support automated campaigns via on-call rotation.

Use statistical modeling and analytical frameworks to shape data acquisition, validation, and ML training strategies for AD/ADAS. Develop metrics to characterize data distribution and diversity, perform ambiguous problem analysis to inform decisions, communicate findings to stakeholders, embed with engineering teams for domain-specific recommendations, and mentor data science engineers to drive best practices.

Design and implement forecasting models and algorithms for pricing and promotions, build features in the forecasting platform, clean and validate data, produce visualizations, write maintainable code, and collaborate with subject-matter experts and clients to translate data into retail business solutions.

Provide technical leadership for enterprise data analytics: design analytical architectures, implement systems and databases, apply statistical and engineering methods, build and optimize SQL analytical structures, guide BI platform selection, ensure data quality and performance, perform tradeoff analyses, collaborate cross-functionally, and communicate findings to non-technical stakeholders.

Own and evaluate national and subnational projection models using large-scale healthcare claims. Build evaluation studies, diagnostic tooling, and benchmarks. Investigate customer-raised anomalies, communicate methodology, review model code with engineering, and maintain documentation to ensure model quality and trust.

Lead applied data science for customer experience by mining structured and unstructured data, designing experiments, building predictive models, and operationalizing solutions. Advance AI/LLM capabilities, mentor data scientists, partner with BI and data engineering to scale analytics, and communicate insights to influence business decisions.

Lead individual-contributor data science work to build predictive models, measurement frameworks, and AI-powered analytics. Partner with Product, Engineering, and Operations to translate insights into product strategy, define success metrics, automate analyses with agentic workflows, apply causal inference and experimentation, communicate findings to executives, and mentor other data scientists.