Top Senior Data Science Jobs

Lead end-to-end data science work: exploratory and statistical analysis, data engineering, ML model development (recommendation engines, predictive systems), data visualization (Power BI, Tableau), and multi-int large-data analytics to support defense programs and produce actionable intelligence products.

Lead Data Scientist responsible for managing projects in data engineering, model design, and infrastructure deployment while collaborating with clients to develop data-driven solutions.

Design and validate statistically defensible data-quality metrics and gap-filling methods for very large, multi-source datasets; benchmark against reference data; specify ingestion and checks; partner with SMEs and engineers to operationalize metrics at scale while preserving privacy and governance.

Lead data science support for investigations and litigation: identify, collect, and analyze business data to detect violations, calculate damages and penalties, advise investigators and attorneys, automate data collection/analysis systems, and support agency research and policy recommendations.

Senior individual contributor who builds statistical models and experiments to optimize acquisition, conversion, retention, and lifetime value. Partners with Product, Marketing, and Engineering to define data requirements, analyze A/B tests, perform cohort and funnel analyses, communicate findings to stakeholders, and mentor junior team members while contributing to analytics best practices.

Seeking a Senior Data Scientist to provide technical expertise for a U.S. Government customer, focusing on data analytics and signals analysis.

The Principal Data Scientist will lead the design of knowledge graph infrastructure in Immunology, standardizing and integrating extensive biomedical data for cross-functional analytics and insights. Responsibilities include data modeling, ontology curation, and collaborating with various scientific teams.

Lead data science efforts for the Program Management Office: optimize and secure SQL databases, build and manage ETL pipelines, create BI dashboards in Tableau/Power BI, automate processes with Python and Airflow, use GitLab in Agile workflows, and perform statistical analysis and data mining to surface trends and insights.

Lead analyst at the Pentagon overseeing a distributed analytics team to standardize, extract, validate, and analyze DoD logistics data. Build automation, predictive models, visualizations, and reports using Python/R/SQL and ML frameworks. Use high-resolution simulation tools and DoD logistics systems to support operational decision-making and mission readiness.

Lead development of mission-ready data exploitation and geospatial analytics solutions using Python. Integrate web APIs, build dashboards and visualizations, query relational databases, use GIS tools, and produce technical documentation. Operate independently at senior level, guide junior staff, collaborate across Intelligence Community analysts, and advise government leadership.

Analyze internal and external datasets to identify macro demand indicators, incorporate macro signals into forecasting, guide forecast biasing, interpret ML outputs, and deliver actionable market insights to planning, FP&A, and leadership.

The Senior Data Scientist will lead data analytics projects, interface with clients, and develop predictive models for business intelligence using various data tools.

As a Senior Data Scientist, you'll design data-driven solutions, analyze performance, collaborate across teams, and communicate insights to drive decision-making.

As a Lead Data Scientist, you will lead a team to develop AI solutions, collaborate with cross-functional teams, design predictive models, and ensure data quality in machine learning pipelines.

The Lead Data Scientist will oversee end-to-end data science projects, develop statistical models and machine learning algorithms, and collaborate across teams to deliver impactful data solutions.

Lead causal inference and marketing mix modeling to measure and optimize marketing investments. Define problems with stakeholders, build statistical pipelines and production models, design and analyze experiments, deploy solutions, and support automated campaigns via science on-call rotation to drive Growth outcomes.

Lead causal inference and marketing mix modeling to measure and optimize marketing investments. Drive end-to-end data science work for Growth: define problems with stakeholders, build statistical pipelines, write production code, design and analyze experiments, deploy production models, and participate in on-call rotations to ensure automated campaigns run smoothly.

Lead measurement and optimization of marketing investments using causal inference and MMM. Deliver end-to-end data science solutions for Growth: define problems, build statistical pipelines, productionize models, design and analyze experiments, own roadmaps, and support automated campaigns via on-call rotation.

Use statistical modeling and analytical frameworks to shape data acquisition, validation, and ML training strategies for AD/ADAS. Develop metrics to characterize data distribution and diversity, perform ambiguous problem analysis to inform decisions, communicate findings to stakeholders, embed with engineering teams for domain-specific recommendations, and mentor data science engineers to drive best practices.

Design and implement forecasting models and algorithms for pricing and promotions, build features in the forecasting platform, clean and validate data, produce visualizations, write maintainable code, and collaborate with subject-matter experts and clients to translate data into retail business solutions.

Lead applied data science for customer experience by mining structured and unstructured data, designing experiments, building predictive models, and operationalizing solutions. Advance AI/LLM capabilities, mentor data scientists, partner with BI and data engineering to scale analytics, and communicate insights to influence business decisions.

Lead end-to-end on-chain data ingestion, attribution, and composability decoding for DeFi surveillance. Build and integrate wallet-clustering feeds, trace funds across chains and bridges, co-develop optimistic-oracle (UMA) surveillance R&D, and deliver versioned on-chain feature tables for detection and validation systems.

Use client platform data to identify trends and actionable insights, define analytical requirements, ensure data quality and governance, and develop statistical, data-mining, and predictive models. Create reports and dashboards, integrate multi-source data, validate accuracy, document processes, collaborate to optimize data systems, implement reusable analytics components, evaluate tools, and train users to support mission-driven, data-informed decision-making.

Lead analysis of large datasets using Databricks to identify trends, model customer retention/churn, create visualizations and dashboards, and integrate AI-driven solutions to support decision-making for consumer and retail analytics.

Lead data science research and develop scalable ML models, audience segmentation, propensity and recommender systems for marketing and eCommerce. Cleanse and integrate large disparate datasets, apply causal inference and A/B testing, define KPIs, ensure data governance and privacy, and communicate insights to product, sales, and marketing stakeholders to drive revenue and product improvements.