Top Data Science Jobs

Analyze large structured and unstructured datasets to build predictive models and automated analytic software. Clean and explore data, develop machine learning solutions, visualize results, and collaborate with clients and teammates to translate insights into actionable decisions. Must hold TS/SCI with polygraph.

Support federal law enforcement by collecting, integrating, analyzing, modeling, and explaining large data to support investigations. Build ML models, perform statistical and graph analyses, create visualizations, communicate results to non-technical stakeholders, and contribute to R&D and shared capabilities while working on-site at government customer locations.

Support critical mission systems by scoping analytical projects, developing workflow use cases, building metrics, dashboards, and visualizations, analyzing operational data for trends and improvements, and collaborating with policy and decision-making stakeholders to translate mission needs into actionable solutions.

Design and implement scalable ETL pipelines and incremental/batch data ingestion. Perform data transformation, validation, modeling, and preprocessing using Python and SQL. Build reusable Python automation packages, automate reporting and dashboards, and document data pipelines and technical procedures.

Provide advanced discovery support using machine learning, statistical analysis, scripting, automation, and TechSIGINT tools. Develop analytical prototypes, create data visualizations, automate workflows, and collaborate with analysts and mission stakeholders to identify patterns and drive investigations.

Analyze large-scale datasets; design, develop, evaluate, and deploy AI/ML and predictive/statistical models; build data models, visualizations, and automated analytical workflows; process data using Spark and cloud platforms; apply TechSIGINT tools and provide discovery-focused analytical prototyping.

Design and automate scalable ETL/ELT and reporting workflows, perform data cleansing/validation/transformation, build reusable Python automation and SQL data-processing pipelines, support dashboard automation, improve data quality and reliability, and document data flows and processes.

Perform advanced data science and machine learning on large NSA/CSS datasets. Design, implement, and validate analytic models, manage and curate data, extract actionable insights, and communicate technical conclusions to non-technical stakeholders. Translate mission needs into technical requirements while staying aware of collection and processing constraints.

Develop and apply statistical and machine-learning methods to large, messy NSA/CSS datasets. Design, implement, and evaluate analytic models; perform data cleaning, management, visualization, and inference; translate mission needs into technical requirements and communicate findings to non-technical stakeholders.

Develop and maintain data ontologies and metrics, analyze large mission datasets with Python/Jupyter/Pandas, automate workflows, build visualizations and dashboards, interact with APIs, identify data/technical gaps, and present findings to government stakeholders.

Perform statistical and computational analysis on large, messy datasets to produce defensible conclusions. Build analytic models, perform statistical inference and prediction, translate mission needs into technical requirements, and communicate results to non-technical stakeholders. Maintain awareness of collection/processing limitations and recommend technical solutions.

Analyze large-scale educational data to inform product design and efficacy. Develop, evaluate, and maintain statistical and AI models, collaborate with cross-functional teams, communicate findings to stakeholders, and leverage AI tools for analysis and feature engineering while following software development practices.

Validate and test credit risk models, prepare validation reports and documentation, support model releases and monitoring, automate model training, perform ad-hoc statistical analyses, and communicate findings to stakeholders to support risk management and production deployment.

Drive product and business analyses across Quora: design and evaluate experiments, build models and visualizations, analyze cross-product data to surface root causes, and partner with cross-functional teams to implement data-informed solutions and frameworks.

Embed with Product and Engineering to define success metrics, design measurement and experimentation frameworks, instrument and monitor launches, translate model-driven signals into decisions, and build repeatable decision loops to convert analysis into shipped changes.

Support digital banking conversion and reporting by creating/validating conversion files, leading UAT, verifying interest calculations, building statistical models (pricing, retention, forecasting, fraud, marketing), managing data architecture and recurring feeds, reconciling data quality, producing ad-hoc analyses, and documenting processes for auditability and operational continuity.

Partner with business leaders to document and deliver company-wide reporting. Maintain and enhance dashboards and data models, build and automate Databricks pipelines/notebooks, ensure data quality, and collaborate with data scientists and engineers to produce actionable enterprise insights.

Design and run statistical and mathematical analyses on diverse data sources to inform leadership decisions. Build datasets, implement repeatable analysis, create documentation and visualizations, recommend system enhancements, and develop performance metrics to assess analytics maturity.

Use data exploration, cleaning, modeling, and visualization to turn structured and unstructured data into actionable insights. Develop predictive models and algorithms, work with clients to define questions, and apply ML/AI/NLP techniques to solve problems. Collaborate across teams and support data-driven decision making.

Lead and scale driver-based revenue models linking product telemetry to financial outcomes. Build forecasting, causal, cohort, and scenario tools; productionize pipelines with monitoring, backtesting, and versioning; partner with Product, Finance, and Analytics Engineering; communicate results to senior leaders and mentor teams to set cross-category modeling standards.

Contract data scientist to remotely gather, extract, and analyze technical information about AI models, benchmarks, data centers, and companies. Tasks include reading ML papers, tracking leaderboards, processing satellite images/permits, compiling infrastructure details, and producing data insights for research and policy. Part-time (10–30 hrs/week), flexible schedule with occasional Pacific Time meetings.

Develop and sustain analytics tools using Python and customer toolset. Apply mathematical, statistical, and computational methods to large, messy national agency datasets, build and validate models, translate mission needs into technical requirements, and communicate complex results to non-technical audiences.

Senior data scientist/exploitation specialist to integrate emerging EO and SAR sensors into NGA Maven pipelines, perform quantitative analysis, build ETL and visualization tools, develop software for labeling campaign management and imagery curation, and support ML model development, partitioning, and evaluation to meet operational intelligence needs.

Design, build, and maintain data architecture and ETL pipelines for emergent sensor and geospatial data. Ensure compliance with government data schemas and NGA governance, manage SQL/NoSQL databases, APIs, metadata, data health alerts, and cross-domain solutions. Support cloud environments, create NPEs and GitLab repositories, perform QC and compliance reporting, and enable data availability for IC consumption and analytics.

As a Staff Data Scientist, you will lead data initiatives, partnering across teams to apply statistical methods and improve mental health care outcomes by translating data into actionable insights.