Top Data Science Jobs

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.

As a Data Scientist, you will perform ETL/data cleaning, develop visualizations, build predictive models, and support AI solution implementation.

Develop and maintain predictive pricing, retention, and conversion models using GLMs and advanced analytics; build monitoring tools for rating performance; support rate filings, product pricing analyses, competitor research, and cross-functional collaboration to inform pricing and enterprise risk decisions.

Design and analyze experiments and causal studies, build retention measurement and predictive models, develop scalable PySpark/SQL data pipelines, create dashboards, and partner with product and growth teams to improve user engagement and retention.

The Data Scientist will analyze data for risk and trading in Daily Fantasy Sports, develop predictive models, and monitor real-time data.

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.

Build and maintain data science models and quantitative measurement frameworks to guide infrastructure decisions (chargers, parking, depots). Analyze infra efficiency and identify improvements. Collaborate cross-functionally with Supply Operations, Product, and Engineering to incorporate business context into model-driven decisions supporting expansion to new territories and cities.

Lead the experimentation science roadmap for Waymo's marketplace platform. Design advanced causal inference and experimental methods for spatial-temporal and network effects, set best practices, partner with engineering to productionize pipelines, and translate results into clear product strategy for stakeholders.

Lead decision science initiatives to improve operational efficiency and financial outcomes. Build decision frameworks, attribution and forecasting models, deliver reproducible Python/SQL code, mentor data scientists, and partner cross-functionally to measure and scale impact.

Lead decision-science initiatives to improve operational efficiency and financial outcomes. Design decision frameworks, attribution and measurement strategies, forecasting and monitoring systems. Produce production-quality Python/SQL code, guide other data scientists, and translate analyses into actionable recommendations for cross-functional stakeholders.

Senior Data Scientist will design, validate, and deploy scalable ML models (recommendation systems, NLP), source and ensure data quality, assess model performance, produce visualizations, collaborate with stakeholders, and mentor junior team members to deliver data-driven solutions that optimize business outcomes.

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.

Assists with analyzing complex datasets, developing predictive models for insurance underwriting, pricing, claims, and retention, and building data pipelines and automated reporting. Collaborates with actuarial, underwriting, claims, product, and data engineering teams to solve business problems. Communicates insights through visualization and data storytelling, monitors model performance and data quality, and explores new data sources and modeling techniques while supporting insurance model governance.

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.

Leads advanced data science and machine learning initiatives for commercial operations in biopharmaceutical oncology. Builds predictive models, segmentation, optimization, patient journey and adherence algorithms, scoring frameworks, and exploratory analyses using claims, sales, real-world, EMR, and commercial datasets. Partners with business stakeholders to translate needs into analytical solutions, supports productionization and data integration, and communicates technical findings to nontechnical audiences.

Lead data science efforts for a defense program onsite in Hazelwood, MO. Define data requirements, build analysis systems, design/deploy ML models, collaborate with engineers and SMEs, mentor junior scientists, ensure security/compliance, and communicate results to stakeholders while improving models and establishing best practices.

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 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.

Develops and enhances financial crime risk models and AI solutions supporting AML/CTF compliance. Collects, prepares, analyzes, and visualizes data; applies statistical modeling and machine learning to uncover insights and solve business problems. Collaborates with analysts, engineers, and developers to build scalable data science solutions, communicates findings to technical and non-technical stakeholders, supports model governance and risk management, and contributes to regulatory and cross-functional initiatives.