Top Senior Data Science Jobs

Provide advanced data science and analytics to support audits, inspections, evaluations, and investigations for a U.S. government agency. Tasks include data acquisition, cleaning, entity resolution, statistical and fraud-risk analysis, dashboard and visualization development, investigative link and timeline analysis, reporting for audits and prosecutions, and supporting data governance, reproducibility, and training for government personnel.

Senior Staff Data Scientist to lead ML/AI strategy and architect scalable ML systems for vehicle quality and engineering analytics. Build predictive, prescriptive, causal, and LLM-based models on large-scale vehicle/IoT data, manage ML lifecycle (training, validation, deployment, monitoring), design experimentation frameworks, and mentor other data scientists to drive measurable quality, warranty, and customer experience improvements.

Senior Data Scientist designs, implements, and maintains data pipelines and ML projects for AFSOC. Responsibilities include analyzing structured and unstructured data, building predictive and NLP models, using big-data frameworks, creating visualizations, coordinating with data engineers, and communicating findings to non-technical stakeholders to drive mission-focused decision making.

As a Data Scientist, you'll curate, optimize data, build ML pipelines, train models, and communicate findings, contributing to national security solutions.

As a Data Scientist at Retool, you will analyze customer behavior and business performance, build analytical models, and provide insights to guide strategy across teams.

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.

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.

The Data Scientist will analyze large datasets using advanced statistical methods and programming to provide insights for strategic organizational decisions. Responsibilities include developing machine learning models, conducting experiments, and collaborating with Data Engineers.

The Data Scientist will create and deliver analytic processes and data solutions while coordinating with clients to address data-related issues. Responsibilities include designing data architecture, building ETL pipelines, integrating APIs, conducting impact analysis, and preprocessing geospatial data.

The Data Scientist will lead advanced analytics and drive decision-making through data engineering, modeling, and visualization, primarily supporting the Air Force's Intelligence mission.

As a Senior Data Scientist, you'll optimize search relevance, retrieve content, analyze data, and collaborate with teams to enhance product strategies.

As a Staff Data Scientist, you will lead experimentation strategies, apply advanced causal inference techniques, and guide analytical insights to drive product and business decisions.

The Data Scientist will lead the development of data products that enable AI-driven insights, ensuring compliance and optimizing processes across CMC workflows.

Lead data science engagements: work with clients to define problems, build ETL pipelines, develop machine learning models and algorithms, create visualizations, guide teammates, and deploy analytic solutions to inform decision-making across classified and unclassified environments.

Design and implement data science solutions: build ETL pipelines, clean and model structured/unstructured data, develop predictive and ML algorithms, create visualizations, lead teammates, and communicate insights to clients. Work often involves classified intelligence data and integration of FOSS/COTS tools.

The Data Scientist will analyze geospatial data, communicate insights, collaborate with teams, and enhance data processes to support national security missions.

As a Senior Data Scientist, you will analyze complex data, develop algorithms, and create insights using machine learning and AI techniques in various sectors, while collaborating closely with clients.

As a Senior Data Scientist, you will analyze complex datasets, develop algorithms, and apply machine learning to solve critical business problems across various sectors while collaborating with clients to provide actionable insights.

Develop complex queries, lead analytics initiatives, and design machine learning models to support decision-making and business insights. Prepare presentations for stakeholders.

Lead risk-focused data science work by analyzing transactions and user behavior, developing automated risk controls and decisioning systems, advising leadership on risk strategy, and partnering cross-functionally to improve risk processes and scalability in a fast-paced fintech environment.

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

The Senior Data Scientist leads data analysis and model development projects, leveraging machine learning to drive insights and solutions. Responsibilities include executing data strategies, developing predictive models, collaborating with teams, ensuring model validity, and guiding junior members in a dynamic environment.

The Data Scientist will transform data into actionable insights using technical expertise in programming and machine learning to improve decision-making and efficiency within teams, while guiding junior personnel.

The Senior Data Scientist will develop machine learning models, conduct A/B tests, and work with behavioral data to enhance customer engagement and partner ROI.

Senior-level data scientist supporting DoD acquisition and sustainment: build predictive, prescriptive, and optimization models; extract insights from structured and unstructured data; engineer and validate ML pipelines; integrate data across classified and unclassified domains; ensure data governance and alignment with DoD data strategy.