Top Data Science Jobs

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.

Lead quantitative analysis and modeling of large real-world health datasets to estimate disease prevalence and incidence. Design statistical and machine learning models, build data pipelines and dashboards, ensure reproducibility and data quality, collaborate with public health experts, and prepare scientific reports and presentations.

Design and implement analytic methods to extract meaning from large, messy NSA/CSS datasets. Build and evaluate models, manage and curate data, translate mission needs into technical requirements, and communicate technical conclusions to non-technical stakeholders while accounting for collection and processing constraints.

Lead Data Scientist responsible for developing and implementing AI and ML solutions to support marketing and business engagement. The role involves technical leadership, model development, data analysis, stakeholder collaboration, and ensuring compliance with governance standards.

Design and lead data science solutions: explore and clean data, build predictive models, perform quantitative analyses, deploy MLOps/GenAI workflows (AWS), visualize results, and advise clients. Guide teammates and deliver solutions for classified/intelligence-related datasets.

Design, build, and deploy predictive models and customer segmentation to optimize Sportsbook bonus spend. Perform end-to-end projects: KPI alignment, data analysis, feature engineering, automation, visualization, and stakeholder communication. Collaborate with Data Engineering to improve pipelines and leverage AI responsibly to drive incremental revenue.

Lead end-to-end clinical outcomes research using large EHR datasets: design observational and quasi-experimental studies, run causal inference analyses, interpret results, publish findings, and partner with clinicians, data science, and commercial teams to shape product and demonstrate impact.

Build, validate, and deploy predictive and statistical models using Python. Perform data extraction, ad hoc analysis, and reporting with SQL and Excel. Collaborate with business partners and Data Engineering to translate business problems into analytical solutions, monitor model performance, and communicate actionable insights.

Perform data exploration, cleaning, analysis, and visualization on structured and unstructured data. Develop predictive models, algorithms, and simulations (Monte Carlo, discrete event, agent-based). Apply ML/AI/NLP techniques, work with clients to define problems, and deliver data-driven insights to inform decisions.

Develop and execute AML transaction monitoring data strategy, build and monitor model performance metrics, investigate data quality issues, define transaction-monitoring specifications with business partners, and address open AML findings to ensure effective anti-financial crime controls.

Analyze large company datasets to generate business insights for product, sales, marketing and leadership. Build, validate and deploy predictive models and algorithms, design A/B testing frameworks, assess new data sources, create data architectures, and coordinate with cross-functional teams to implement and monitor model performance and outcomes.

The Data Scientist will analyze complex datasets, develop predictive models, and collaborate with stakeholders to drive data-driven decisions.

SOSi is seeking a Data Scientist to develop AI/ML models, handle petabyte-scale data, and utilize Python and SQL to automate national security tasks.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

The Data Scientist will support analytics initiatives, collaborating across functions to build models, map data, and solve business problems using data science techniques.

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

Partner with Product and Engineering to define product metrics, design experiments and causal analyses, build reporting and models, analyze user behavior and segments, and translate insights into product recommendations while establishing Product Data Science practices.

The role involves building the marketing data science function, developing metrics, dashboards, and models to analyze marketing effectiveness, and fostering a data-informed culture.

Lead pricing analytics as the first dedicated data scientist on the Pricing team. Design analyses, causal models, experiments, and decision frameworks linking usage, conversion, retention, and revenue to guide pricing, packaging, discounts, and monetization across consumer, SMB, and enterprise segments. Communicate executive-ready recommendations and build a repeatable pricing data science function.

Work on-site in a SCIF to design and implement data science solutions for DoD cyber risk management. Lead development of algorithms, build ETL pipelines, structure unstructured data, draft analytics documentation and use cases, mentor junior analysts, and communicate findings to technical and executive stakeholders.

Design and evaluate causal inference experiments and causal ML models to measure product impact, optimize resource allocation, and inform support operations. Build, deploy, and iterate statistical/ML models, analyze tradeoffs, collaborate cross-functionally, and communicate insights to influence decisions and scale data science capabilities.

Support data analysis, prepare data for exploratory analysis, contribute to model building and validation, assist metadata and ETL tasks, and create visualizations to communicate model insights.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

The Senior Data Scientist analyzes semiconductor manufacturing data, develops predictive models, collaborates with teams for process optimization, and creates data visualizations to enhance product performance.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.