Top Data Science Jobs

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Lead product-focused analyses across growth, retention, creator and economy verticals. Define metrics and experiments, analyze user and creator behavior, build dashboards and reusable analytical assets, use AI-assisted workflows to accelerate analysis, collaborate with engineering to improve data quality, and communicate insights to influence product decisions.

The Lead Data Scientist will oversee AI projects, mentor engineers, and develop systems for knowledge retrieval and analysis in defense. Responsibilities include guiding technical strategy, collaborating across teams, and championing AI innovations.

The Lead Data Scientist will lead AI solution development for National Security by driving projects, mentoring teams, and enhancing systems with advanced simulation and optimization techniques.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

Lead end-to-end data science work: exploratory and statistical analysis, data engineering, ML model development (recommendation engines, predictive systems), data visualization (Power BI, Tableau), and multi-int large-data analytics to support defense programs and produce actionable intelligence products.

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

Lead analyst at the Pentagon overseeing a distributed analytics team to standardize, extract, validate, and analyze DoD logistics data. Build automation, predictive models, visualizations, and reports using Python/R/SQL and ML frameworks. Use high-resolution simulation tools and DoD logistics systems to support operational decision-making and mission readiness.

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.

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.

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.

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.

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.

Lead analysis of large datasets using Databricks to identify trends, model customer retention/churn, create visualizations and dashboards, and integrate AI-driven solutions to support decision-making for consumer and retail analytics.

Use client platform data to identify trends and actionable insights, define analytical requirements, ensure data quality and governance, and develop statistical, data-mining, and predictive models. Create reports and dashboards, integrate multi-source data, validate accuracy, document processes, collaborate to optimize data systems, implement reusable analytics components, evaluate tools, and train users to support mission-driven, data-informed decision-making.

Lead end-to-end data science initiatives across pricing, dispatch, ETA, routing, and forecasting. Turn ambiguous logistics problems into production ML solutions, build data pipelines, partner with engineering to deploy models, establish evaluation and A/B testing, and work directly with customers and leadership to measure business impact.

Own statistical methodology for mission engineering: design experiments for large-scale simulations, apply Bayesian and regression methods, build scalable Python data pipelines and surrogate models, quantify uncertainty and sensitivity, produce decision-quality visualizations and reports, mentor teams, and support DoD/DARPA/intelligence programs.

Lead and execute complex analyses of large-scale health care claims, build data pipelines and analytic infrastructure, ensure data quality and reproducibility, manage projects and timelines, mentor junior staff, and translate results into policy-relevant insights.

The Senior Data Scientist will develop and deploy machine learning models for yield optimization, pricing, and inventory allocation in programmatic advertising. Responsibilities include building data pipelines, real-time inference systems, conducting experiments, and collaborating with product and engineering teams to enhance marketplace performance.