Top Data Science Jobs

The Data Scientist will analyze data using machine learning and statistical methods to deliver insights, develop algorithms, and support customers with analytical discussions.

Lead end-to-end data science initiatives across pay TV, digital products, media sales, and customer lifecycle. Design, deploy, monitor ML/AI solutions (churn, propensity, personalization, recommendation, forecasting), partner with stakeholders, build data pipelines, run experiments (A/B, uplift), mentor teams, and translate analytics into measurable commercial impact.

The Staff Data Scientist will lead data science projects, build ML models, develop AI solutions, and mentor junior staff while integrating data-driven insights into business operations.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

The Bioinformatics Data Scientist will analyze multi-omics data, develop methods, build tools, and communicate findings to support drug development decisions.

Design and implement statistical, ML, and geospatial models to extract actionable intelligence from large structured and unstructured datasets. Perform EDA, feature engineering, model evaluation, and operationalization on cloud-native secure platforms. Produce visualizations, dashboards, documentation, and collaborate with engineers, architects, and mission stakeholders to gather requirements and integrate analytical capabilities into operational systems.

The Staff Data Scientist leads machine learning initiatives for personalization and optimization. Responsibilities include causal measurement, LTV model development, and technical leadership across data science teams, partnering with cross-functional teams to align strategies and impact revenue outcomes.

As a Data Scientist, you will generate insights to prioritize efforts and identify opportunities, focusing on experimental and causal inference methodologies.

Build and deploy credit risk models for acquisition and account management. Create datasets and features from traditional and non-traditional sources, collaborate with credit, product, and engineering partners, run experiments, and monitor models in production to enable responsible lending decisions.

The Data Scientist will assist in developing AI and data science solutions, focusing on data analysis, model development, and collaborating with cross-functional teams, while under supervision and mentorship.

Use data science to source, ingest, clean, transform, analyze, and visualize structured and unstructured data in WDP. Develop dashboards and data products (Databricks, SQL, Python, Tableau/Qlik), create visual narratives, and brief senior DoW leadership to support IT portfolio management.

Lead data science efforts: explore, clean, analyze structured and unstructured data; design data pipelines; build predictive models and visualizations; guide teammates and advise clients. Communicate findings at strategic and technical levels.

As a Data Scientist, you will analyze data to provide insights, develop algorithms, and solve complex problems using machine learning and scientific methods.

Design and lead development of ML and AI solutions: explore, clean, analyze structured and unstructured data, build predictive models, apply NLP/text-mining techniques, integrate enterprise systems, visualize results, and advise clients while guiding teammates.

Data Scientist role focused on leveraging IoT, machine learning, and AI to analyze complex datasets for actionable insights across various sectors.

Perform data science for defense intelligence: collect/clean data, build statistical and ML/NLP models, code in Python/SQL on AWS, produce dashboards/reports (Tableau), and support analysts. Work independently on moderate-complexity problems; active TS/SCI with polygraph required.

Data Scientists develop and maintain AI software and systems, focusing on machine learning algorithms, model deployment, and data analysis for predictive maintenance and failure prediction.

Lead data science work with clients: analyze structured and unstructured data, develop predictive models and NLP solutions, visualize results, integrate enterprise systems, and guide teammates to deploy AI/ML workflows that inform decisions.

Lead company-level measurement and causal strategy, define MAU×ARPU metrics and semantic mart, set scientific standards for experimentation and analysis, own strategic models (MMM, elasticity, forecasting), partner with engineering to productionize analytics, and raise org-wide scientific maturity through governance, templates, and upskilling.

Contribute to data pipelines, validate and refine analytical models, perform advanced analyses and data quality checks, collaborate with cross-functional teams, and write maintainable analytical code and documentation to support business decision-making.

Perform data science on classified datasets: build and evaluate ML/AI models (including LLMs/agentic AI), clean and retrieve data, visualize findings for non-technical leaders, and support DoW/IC clients while holding required security clearance.

Mid-level data scientist who partners with clients (DoD/IC), analyzes large structured and unstructured datasets, evaluates and tests AI/ML models, mentors teammates, and delivers actionable insights to leadership to improve data science capability.

Build full-stack data science solutions for finance: develop, test, and ship models; partner with data engineering and finance teams to create actionable financial insights; drive experimentation and analytics best practices; produce dashboards and reports to influence business decisions.

Perform epidemiologic analyses on surveillance, clinical, claims, lab, and survey data; develop analysis plans, statistical methods, and technical reports; build dashboards and automated analytic workflows; design data quality rules and surveillance indicators; translate findings for diverse stakeholders; support public health reporting, manuscripts, and dissemination; mentor junior staff and provide technical assistance.

Lead and mentor a data science team to design, build, and deploy advanced analytics and AI/ML solutions (including LLMs/agentic AI) for classified DoD/IC clients. Translate complex data into visual and written narratives, advise leadership on risks and go/no-go criteria, and identify new data-driven opportunities. Work includes data retrieval/cleaning, modeling, evaluation, and visualization.