Top Data Science Jobs

Supports business strategy through statistical analysis, experimentation, data mining, and machine learning. Partners with business and IT teams to prepare datasets, identify process-improvement opportunities, and build predictive and computer vision models. Applies advanced statistical methods, develops testing scenarios, evaluates model performance, communicates insights to stakeholders, and supports model deployment and enhancement.

Leads data science initiatives by exploring, cleaning, analyzing, and visualizing structured and unstructured data. Develops predictive models, algorithms, quantitative analyses, and machine learning or NLP solutions to address client challenges. Collaborates with clients, provides data-driven recommendations, leads complex projects and deliverables, mentors team members, and identifies opportunities to apply data science to public- and private-sector problems.

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.

Develop predictive models, quantitative analyses, visualizations, and data workflows using Palantir Foundry or Gotham. Analyze structured and unstructured data, transform siloed information into actionable intelligence, and advise national security clients on data-driven decisions. Collaborate with engineers, analysts, and mission stakeholders to solve complex programs and support mission-critical applications.

Uses statistical programming, machine learning, artificial intelligence, and natural language processing to explore, clean, analyze, visualize, and model structured and unstructured data. Develops algorithms, predictive models, quantitative analyses, and data-driven systems while collaborating with clients and teammates to solve complex challenges across public and private sectors. Requires a bachelor's degree and TS/SCI clearance.

Leads data science architecture and advanced analytics for government intelligence missions. Develops scalable Python pipelines, geospatial and multi-INT analytics, machine learning models, network analysis, and interactive dashboards. Translates intelligence requirements into production solutions, mentors data scientists, researches innovative methodologies, and delivers GEOINT products aligned with NGA and DNI standards.

Designs AI risk stratification and evaluation methodologies for Veterans Health Administration systems, assessing performance, fairness, value, and post-deployment monitoring. Provides technical guidance on machine learning, healthcare data models, cohorts, synthetic data, and pilot evaluations. Develops risk management materials and supports governance decisions through quantitative analysis. Requires extensive applied data science experience, advanced education, and expertise in healthcare-focused machine learning.

Lead statistical modeling, AI/ML evaluation, data governance, data quality assurance, and executive analytics for VA EHR modernization. Build reproducible R-based analytics, reporting pipelines, dashboards, and governed data products using R, SQL, Python, Git, and cloud platforms. Evaluate model reliability, bias, drift, and operational value; integrate complex healthcare data; define metrics and validation rules; and advise stakeholders on auditable analytical practices.

Leads end-to-end data science initiatives, developing and deploying scalable machine learning and AI solutions for crop protection product development. Responsibilities include opportunity identification, data preparation, model development, evaluation, production deployment, emerging AI technology evaluation, stakeholder collaboration, technical leadership, mentoring, and communicating analytical insights.

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.

Architect and develop voice-based chat, NLP, LLM, speech-processing, and natural-language search solutions for public safety applications. Build structured-data extraction, parsers, chatbots, REST APIs, cloud services, data governance, and optimized database queries. Develop multilingual, STT, and TTS datasets; fine-tune models; manage cloud provisioning; and mentor interns and junior data scientists.

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.

Develops advanced analytics, mathematical models, algorithms, simulations, and software tools for Army mission data. Responsibilities include processing large datasets, creating and evaluating machine learning models, supporting MLOps frameworks, researching analytics tools, and enhancing applications for defense customer missions.

Performs data science and big data platform work, including machine learning, algorithm development and refinement, advanced statistical analysis, data mining, data modeling, data management, visualization, and analytics. The role supports multiple domain areas and requires advanced computational expertise, a qualifying degree, substantial relevant experience, and an active TS/SCI with polygraph clearance.

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.

Develop mathematical, statistical, and machine learning models to solve complex problems across multiple domains. Analyze datasets, automate tasks, communicate analytical results, and align solutions with customer and management objectives. The role supports defense and space-related programs, requires collaboration with government and contractor teams, and is performed onsite in Colorado Springs.

Collects, explores, and analyzes large datasets to identify business opportunities and improve outcomes. Develops predictive models, machine-learning algorithms, testing frameworks, and data pipelines; evaluates data quality and model performance; and communicates actionable insights to stakeholders and clients. The role also manages data science projects, establishes reporting best practices, and collaborates with cross-functional teams to implement and monitor solutions.

Develop and maintain credit risk, repayment, and predictive models powering financial products. Engineer features from transaction data, deploy and monitor production ML models using AWS and Snowflake, analyze model performance and drift, prototype modeling methods, and collaborate with product, risk, and engineering teams. Communicate findings to technical and non-technical stakeholders while applying explainable AI, time-series modeling, and financial machine-learning best practices.

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.

Analyze, clean, and validate complex healthcare data; develop statistical, machine learning, and AI models; implement agentic workflows, RAG solutions, and model fine-tuning; deploy and monitor models in production; collaborate with technical and business teams; conduct research; and document and communicate findings.

Leads the design and evolution of scalable statistical computing platforms, automation workflows, reusable programming tools, and data visualization capabilities for clinical development. Provides technical strategy, architecture guidance, regulatory-aware solutions, and leadership across global, cross-functional initiatives. Advises senior stakeholders, drives standards and tool adoption, resolves complex scientific computing challenges, and mentors teams. The role supports reproducible, compliant, high-performance evidence generation using Python, R, and advanced data science practices.

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.

Develop predictive models, algorithms, quantitative analyses, and data visualizations from structured and unstructured data. Explore, clean, analyze, and interpret complex datasets using statistical programming, machine learning, NLP, and text-mining techniques. Collaborate with clients to identify data-driven solutions, lead solution development for complex programs, guide teammates, and provide insights supporting informed decisions.

Develop algorithms, predictive models, and data-driven systems using structured and unstructured data. Perform data exploration, cleaning, analysis, visualization, mining, and modeling to answer client questions and support informed decisions. Apply statistical programming, machine learning, artificial intelligence, and natural language processing techniques across public- and private-sector challenges. Collaborate with clients in data-rich environments and translate complex datasets into objective, actionable insights.