Top Data Science Jobs

Perform exploratory data analysis, clean and analyze structured and unstructured data, develop predictive models and visualizations, and communicate insights to technical and non-technical stakeholders. Use appropriate tools and frameworks to turn disparate data into actionable recommendations for clients.

Apply data science and ML techniques to large structured and unstructured datasets to support DoD strategic decision-making. Perform statistical analyses, build production-quality visualizations and dashboards, lead projects from scoping to delivery, mentor junior staff, collaborate with stakeholders, and communicate insights to senior leadership using distributed computing and reproducible analytic workflows.

As a Senior Data Scientist, you will analyze complex data sets, develop predictive models, and guide clients in decision-making through data visualization and insights.

GliaCell seeks a Data Scientist with experience in software development and strong communication skills. Responsibilities include data analysis, modeling, and working with government contracts. Must possess a TS/SCI clearance and programming expertise in Python and R.

As a Data Scientist, you will shape data science efforts, work with teams to understand product usage, mentor junior staff, and build data products.

Lead forecasting, budgeting, and LTV modeling for eCommerce; develop demand and customer-behavior models; validate A/B tests; drive AI/LLM adoption and prototype solutions; translate analyses into executive-ready insights and partner with Finance, Product, and Marketing.

Lead forecasting, budgeting, LTV and retention modeling, and advanced analytics for eCommerce. Drive AI/LLM adoption, build prototypes and scalable solutions, validate A/B tests, partner cross-functionally, and translate analyses into executive-level narratives to inform strategic decisions.

Support government analytics for integrated combat and weapons systems using MATLAB or Python. Analyze test data, develop automation scripts, produce technical reports and visualizations, collaborate with multidisciplinary teams, and improve data analysis workflows under government direction.

The Data Scientist will develop AI/ML models to enhance healthcare processes, ensuring compliance and quality in clinical documentation.

Perform end-to-end data science for underwriting, auto-quoting, and sales analytics: detect emerging risks, quantify data blind spots, build multi-signal models and confidence scoring, measure algorithmic impact on sales, and maintain ingestion and pipeline data quality and monitoring.

Lead development of automated, auditable revenue data pipelines and anomaly detection to improve reconciliation and data integrity. Build reusable financial data assets, dashboards, and reports; collaborate with finance and cross-functional teams to support month/quarter-end close and audit readiness.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Analyze complex gameplay and engagement datasets to identify trends and opportunities. Build and maintain statistical and predictive models, dashboards, and visualizations. Collaborate with game designers, product managers, and engineers to define data-driven strategies, ensure data quality, and communicate insights to stakeholders. May supervise junior staff.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

As a Senior Data Scientist, you will develop technologies for signals exploitation, perform data analysis, and implement algorithms while collaborating with project teams.

Lead a 5–8 person Data Science team to develop and operationalize FWA detection models using SAS and Python on multi‑payer healthcare claims. Oversee model development, data pipelines, quality reviews, stakeholder presentations, and collaboration with SMEs and BI developers. Split role ~40% management, 60% hands-on coding/analysis.

Embedded on a core business team, the Associate Data Scientist defines problems, builds metrics/reports, runs analyses and experiments, surfaces insights, and drives data-informed recommendations end-to-end to impact growth, product, AI/automation, or partnerships.

Design, develop, and operationalize Python-based analytic pipelines and interactive dashboards integrating structured and unstructured data to support DoD/IC missions. Modernize legacy workflows for scalability and reproducibility, lead analysis and automated processes, and serve as a senior SME coordinating with clients on data-driven solutions in high-consequence environments.

Embedded on a core business team, define and prioritize analytical problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed product, growth, and partnership decisions end-to-end.

Embed with a core business area to define right problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to improve product, growth, AI, or partnerships.

Design, build, and maintain databases, ETL pipelines, and cloud-based data architectures; enforce data governance and metadata standards; develop API workflows for sensor data movement; perform data cleansing, QC, and automated analytics to support intelligence community consumption and compliance.

Embed with a core business area to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across product, growth, AI/automation, or partnerships.

Embedded within a business unit, the Data Scientist defines the right problems, builds metrics, analyses, reports, and experiments, and delivers data-driven recommendations and end-to-end execution to improve product, growth, AI/automation, or partnerships.

Embed in a core business area to define problems, build metrics, run analyses and experiments, surface insights, and drive outcomes by recommending and executing data-driven actions end-to-end.

Work embedded in a business unit to define problems, run analyses, build reports and experiments, surface insights, and drive data-informed decisions end-to-end with product, growth, AI, or partnerships teams.