Top Data Science Jobs

Senior Data Scientist supporting Intelligence Community operations. Build customized visualizations and analytic applications using Esri and Python, automate analytic workflows, apply AI/ML to structured and unstructured data, and clearly communicate technical results to stakeholders.

Lead development and deployment of scalable data science and ML solutions to detect and mitigate fraud, automate workflows, analyze behavioral signals, run experiments, build dashboards, and partner with stakeholders, legal, and compliance to measure KPIs and integrate models into decision systems.

Support predictive modeling and spatial analytics to inform member growth, market potential, and branch strategy. Clean and integrate large datasets, engineer features, build reproducible pipelines, validate models, collaborate with GIS analysts, and deliver insights and visualizations to technical and business stakeholders.

Develop and apply mathematical, statistical, and computational methods to extract insights from large, messy NSA/CSS datasets. Design and implement machine learning and analytic models, perform data cleaning and management, communicate results to non‑technical stakeholders, and translate mission needs into technical requirements while accounting for classification and system constraints.

Collect, clean, validate, and analyze metrology, manufacturing, and business data. Create visualizations, reports, and dashboards, apply statistical methods, automate reporting processes, monitor data quality, and collaborate with engineering and operations to drive data-driven improvements.

Lead and build Neural Earth's geospatial data science function: design and deploy Python-based geospatial models, architect production geospatial data pipelines, validate reproducible methods, translate scientific outputs into customer-ready products, and manage and mentor at least one direct report while advising customers and stakeholders.

Support NGA mission operations by applying Python and SQL to analyze GEOINT and multi‑INT data, develop and test analytic methodologies and machine learning approaches, identify patterns across complex datasets, and deliver actionable intelligence to government stakeholders while maintaining accuracy and quality.

Perform intermediate-to-advanced data analysis, build predictive/prescriptive components, create dashboards and reports, collaborate with business and technology partners to operationalize insights and optimize operations.

Use real-time and historical healthcare data to prepare, clean, analyze, and visualize metrics and dashboards (Tableau). Extract data via SQL, interpret results, share insights and recommendations with internal and external stakeholders, respond to ad-hoc analytics requests, and ensure deliverable quality through peer review.

Develop and maintain automated data pipelines, build predictive models and metrics for player/team performance, support data ingestion with engineers, create dashboards and visual apps, conduct research projects, and communicate insights to coaching and club stakeholders across multiple clubs.

Internship role to develop and deploy user-growth algorithms: user segmentation, recommendations, LTV/churn/conversion models, A/B testing, causal inference analyses, and collaborate with product and engineering to drive measurable growth.

Design, refine, and operationalize geospatial analytic models; structure GEOINT attributes into defensible scoring frameworks; automate workflows and build dashboards; integrate models with analytic platforms (ArcGIS); work with analysts and leadership to ensure tradecraft integrity, transparency, and repeatable mission-focused outputs using Python and SQL.

The Data Scientist will collaborate with teams to shape product strategy using machine learning and econometric models on large datasets, measuring outcomes and designing data-driven solutions.

The Data Scientist will conduct data research, develop analytics models, ensure data quality, and communicate actionable insights to stakeholders. Responsibilities include statistical analysis, data mining, and collaboration with business experts to enhance decision-making.

The Data Scientist Level 3 will analyze large datasets, develop strategies for data extraction, and communicate findings. Required experience includes machine learning and programming.

Analyze large marketing datasets, build predictive models for segmentation, pricing, and demand forecasting, support targeted campaigns and retention, partner with product and marketing, apply statistical and ML methods, ensure data quality with engineering, and communicate insights to stakeholders to drive conversion and retention improvements.

Lead end-to-end data science projects: define problems, build/test hypotheses, deliver scalable solutions for productization. Perform advanced statistical and time-series analyses, collaborate cross-functionally, and translate insights into customer value while supporting deployment and system optimization.

Lead design and implementation of scalable workflows to transform large geospatial/intelligence data into mission-ready analytic products. Script in Python, produce operational visualizations, provide senior-level direction and QA, and collaborate across NGA and IC to support intelligence operations.

The Data Scientist will develop performance evaluation frameworks for autonomous vehicles, using statistical models and metrics to ensure quality and safety of the Waymo Driver, while collaborating with engineering teams on simulation data and product readiness.

Seeking a QlikView/Java expert with over 10 years of experience in data visualization and model development using QlikView. Responsibilities include dashboard creation, data integration, and administration of QlikView tools.

The Data Scientist at GenLogs will build machine-learning systems, analyze large datasets, and collaborate with engineering and product teams to deliver advanced logistics intelligence solutions.

The Data Scientist will build AI-driven fraud and risk systems, work with real-world data, and leverage graph techniques to improve detection and labeling. They will partner with engineering to scale data systems in the compliance domain.

The Data Scientist will analyze claims data, develop predictive models, and work with unstructured data using R and Python in a financial services context.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

Seeking a Data Scientist with expertise in Full stack Development and AWS Architecture for a 3-6 month local project.