Top Data Science Jobs

The Data Scientist will design and implement machine learning algorithms for enterprise applications, collaborate with federal customers, and contribute to the C3 AI Suite's features.

Translates stakeholder requirements into automated, data-driven solutions. Designs end-to-end workflows for data ingestion, storage, transformation, quality, governance, and delivery across structured and unstructured data. Modernizes data environments, improves accessibility and lineage, and reduces manual processes using Microsoft 365 and related platforms. Collaborates across teams in an agile environment, prioritizes development work, tracks progress, and advises stakeholders on data strategy and AI readiness.

Designs and maintains large-scale analytic solutions using ECL and HPCC Systems. Develops data models, scalable ingestion and transformation workflows, and analytical methodologies for clustered and distributed computing environments. Uses Python, R, Pig, Java, C, and SQL for parallel data processing. Collaborates with engineers, analysts, and mission stakeholders while validating data quality, analytical methods, and outputs. Requires extensive experience supporting national security analytics.

Conduct statistical analysis, media measurement, experimentation, and campaign optimization using Python, SQL, and advanced analytics. Translate client objectives into measurement strategies, manage datasets, develop reproducible analyses, create dashboards and reports, and present actionable insights. Independently manage workstreams, collaborate with data scientists and engineers, support productionization of tools, and serve as a key client contact for campaign measurement, optimization, and data infrastructure.

Build and own marketing measurement, experimentation, attribution, dashboards, and insights across paid, influencer, UGC, and lifecycle channels. Analyze CAC, ROAS, payback, cohorts, LTV, campaign performance, and incrementality. Debug tracking gaps, develop attribution taxonomies and instrumentation, run tests, and translate findings into clear recommendations for marketing, product, data, and finance leaders.

Develops end-to-end machine learning solutions for pricing, forecasting, optimization, customer journey efficiency, and business growth. Responsibilities include data collaboration, A/B test design, classical and deep learning, time series and uplift modeling, error analysis, production preparation, model monitoring, and stakeholder communication.

Lead web and marketing analytics: define tracking specs, implement and validate scalable tracking, join web and game data, build dashboards and reports, deliver campaign-level insights, measure feature effectiveness, and partner with stakeholders to make data actionable.

Work as a healthcare data scientist/consultant delivering statistical analysis, predictive modeling, BI reporting, and data visualization for clients. Independently manage projects and client relationships, using R, SAS, SPSS, Cognos, and BusinessObjects. Report to the Senior Consultant.

Consulting role performing statistical analysis, predictive modeling, BI reporting, and data visualization for healthcare clients. Independently manage projects and maintain client relationships while reporting to a Senior Consultant.

Serve as a healthcare data scientist/consultant performing statistical analysis, predictive modeling, BI/reporting, and data visualization using R/SAS/SPSS and BI tools. Work independently on client projects, maintain client relationships, and report to the Senior Consultant.

Perform healthcare analytics and predictive modeling using statistical tools; develop business reports and visualizations; use R, SAS, SPSS, Cognos, and BusinessObjects; work independently on projects and maintain client relationships while reporting to a Senior Consultant.

Serve as a healthcare data science consultant, independently leading projects and client relationships. Use statistical tools, predictive modeling, BI/reporting, and data visualization (R, SAS, SPSS, Cognos, Business Objects) to deliver analytic insights for healthcare clients, reporting to a Senior Consultant.

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.

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.

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.

Leads advanced analytics, machine learning, statistical modeling, and NLP solution development using healthcare and operational data. Builds scalable pipelines, visualizations, and deployed models on Google Cloud Platform, translates findings for clinical and executive leaders, designs experiments, and establishes performance metrics. Requires collaboration across clinical, technical, and data engineering teams, with occasional on-site travel for executive presentations.

Designs and implements AI solution architectures for Marine Corps operational needs. Develops innovative machine learning solutions, selects algorithms and technologies, builds data-processing scripts and programs, and supports scalable data platforms. Collaborates with cross-functional teams, advises clients on ML tools and frameworks, and may mentor team members. Requires software engineering experience, big data expertise, a programming language, a bachelor’s degree, and eligibility for a Secret clearance.

Leads Central Health System’s data science team and serves as its senior technical authority. Develops and validates predictive, machine learning, NLP, and forecasting models supporting population health, care management, and clinical decision-making. Oversees AI governance, model risk assessment, fairness, reproducibility, documentation, and regulatory alignment. Partners with clinical, data engineering, governance, and analytics teams while mentoring staff and managing advanced analytical standards across Epic, Azure, Snowflake, and other enterprise data sources.

Develops pricing and promotion optimization models using forecasting, deep learning, predictive modeling, and advanced analytics. Leads analytics solution development, interprets large datasets, communicates recommendations to technical and business audiences, and collaborates with cross-functional partners. The role also builds reusable algorithms, documents analytical solutions, and explores new data science techniques to improve profitability, efficiency, and customer experience.

Own product analytics across Axon’s ecosystem, partnering with product managers to define metrics, validate tracking, build durable data models, and deliver decision-focused analyses. Apply segmentation, experimentation, forecasting, and causal inference to product adoption and engagement questions. Help establish shared metric and reporting standards, maintain data quality and documentation, and explore AI agents for querying, anomaly detection, and insight generation.

Own network cost unit economics by building and optimizing plan configuration models, validating them against carrier invoices and financial data, forecasting usage and spend, and supporting pricing and contract decisions. Move recommendations into automated, auditable workflows, maintain dbt and Redshift data models, investigate discrepancies, and communicate quantified business impacts.

Build coupled fusion-device simulation models, radiation and surrogate models, diagnostic data pipelines, Bayesian inference systems, and uncertainty quantification tools. The role covers pulsed-power circuits, plasma dynamics, neutron and X-ray production, machine lifetime modeling, and HPC-enabled computation. The scientist will write production-grade numerical software, validate models against experimental diagnostics, document assumptions, and eventually grow a simulation team.

Develop algorithms, predictive models, quantitative analyses, and visualizations using structured and unstructured data. Apply machine learning, artificial intelligence, natural language processing, statistical programming, and data mining to help clients solve complex problems across public and private sectors. Collaborate with clients to understand needs, uncover insights, and transform disparate data into actionable information. The role requires a Secret clearance and a bachelor’s degree.

Build predictive and cohort models supporting underwriting and marketing. Source, evaluate, combine, and analyze internal and external data; develop analytical datasets and solutions; implement and monitor models in production; communicate insights to business partners; document methodologies and results; and support statistical analysis requests. May supervise 1–2 analysts and provide guidance on cohort modeling and related analytics techniques.

Senior Data Scientist partnering with Product, Engineering, and Design teams to analyze user behavior, product performance, and marketplace dynamics. Responsibilities include developing metrics and reporting frameworks, designing experiments, diagnosing business trends, analyzing marketplace behavior, and aligning stakeholders on analytical priorities. The role uses SQL and Python alongside BigQuery, dbt Cloud, Airflow, Tableau, and Statsig, with a focus on product analytics, experimentation, and data-informed decision-making.