Top Data Science Jobs

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.

Build and validate predictive and causal inference models from messy healthcare commercial data; translate models into dashboards/scoring systems; partner with marketing, market access, and commercial teams to inform strategy and deploy model-driven decisions.

Own revenue and product analytics: build KPIs, dashboards, dbt-style data models, run product/usage experiments, partner with GTM, and deliver executive insights to scale revenue operations.

Turn raw customer supply-chain data into structured representations and models. Interpret and contextualize noisy data, form and test hypotheses, build inference, regression, simulation and optimization logic, validate model quality in production, and translate scientific requirements into engineering specifications while collaborating with data engineers and supply-chain experts.

Lead data science engagements: work with clients to define problems, build ETL pipelines, develop machine learning models and algorithms, create visualizations, guide teammates, and deploy analytic solutions to inform decision-making across classified and unclassified environments.

Design and implement data science solutions: build ETL pipelines, clean and model structured/unstructured data, develop predictive and ML algorithms, create visualizations, lead teammates, and communicate insights to clients. Work often involves classified intelligence data and integration of FOSS/COTS tools.

As a Senior Data Scientist, you will develop and deploy machine-learning models, collaborating with teams to enhance data systems' performance and quality.

The Senior Data Scientist will develop analytics solutions to transform healthcare data into actionable business insights, influencing product strategy and decision-making for CVS Health.

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

Lead data science work on the Matching team: translate product goals into analytics and ML problems, design and analyze A/B tests, mine data for product insights, and collaborate to develop and test production models that improve user matching.

The Data Scientist will analyze geospatial data, communicate insights, collaborate with teams, and enhance data processes to support national security missions.

Maintain and enhance risk models, data fields, code, and dashboards to identify at-risk agency partners. Calculate health scores, validate automated rankings, aggregate and analyze findings, prepare materials for risk meetings, track action items, and present results to management and non-technical stakeholders.

As a Lead Data Scientist, you will design and implement scalable data pipelines and analytics capabilities while leading technical decisions across data workflows, ETL processes, and statistical modeling in the GCP environment.

The Senior Data Scientist develops quantitative models for financial crime compliance, performs data analysis, and collaborates across teams to enhance model performance.

Lead a data science team to build predictive models, perform large-scale data analysis, collaborate with stakeholders and engineering to deploy models, manage projects, and translate insights into business recommendations.

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.

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

The Senior Data Scientist leads data analysis and model development projects, leveraging machine learning to drive insights and solutions. Responsibilities include executing data strategies, developing predictive models, collaborating with teams, ensuring model validity, and guiding junior members in a dynamic environment.

The Senior Data Scientist will develop machine learning models, conduct A/B tests, and work with behavioral data to enhance customer engagement and partner ROI.

Senior-level data scientist supporting DoD acquisition and sustainment: build predictive, prescriptive, and optimization models; extract insights from structured and unstructured data; engineer and validate ML pipelines; integrate data across classified and unclassified domains; ensure data governance and alignment with DoD data strategy.

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.

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.

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.