Top Data Science Jobs

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

Build, validate, and productionize clustering and attribution heuristics on large multi-chain on‑chain datasets. Own end-to-end data pipelines, investigate edge cases (mixers, bridges, consolidation), benchmark against ground truth, and partner with investigations and product to define and defend precision/coverage metrics.

The Bioinformatics/Data Scientist will analyze multi-omics data from organoid systems, develop computational pipelines, and collaborate on research to optimize protocols and interpret results.

Design and develop methods for analyzing big data to generate insights for healthcare applications, using statistical methods and machine learning. Collaborate across teams to improve predictive modeling and data utility.

The Data Scientist will analyze large datasets, design statistical systems, and build models to aid government clients in decision-making. Responsibilities include applying predictive modeling, optimizing processes, and collaborating on agile teams.

Support a federal client by cleaning and ETLing data, performing analysis, building Databricks pipelines and visualizations, and developing predictive models. Maintain governance, Unity Catalog, and workspace administration.

Lead data scientist for Mobile Consumer Create, partnering with product, engineering, and design to set strategy and roadmap. Design and run experiments, analyze user behavior to identify engagement "magic moments," define success metrics and frameworks, and help build strong data foundations for the mobile app.

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

As a Data Scientist II at Oscar, you'll drive data science projects, develop models, collaborate with cross-functional teams, and ensure quality outputs with minimal oversight.

As a Data Scientist II, you will own data science projects, drive analytical work, and collaborate on impactful solutions in insurance data analytics.

The Data Scientist II will drive projects in data science, manage analytics and modeling work, and collaborate closely with cross-functional teams.

The Data Scientist I will implement strategies on a decision-making platform, support product development through data-driven insights, and enhance risk and revenue strategies using data modeling techniques.

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

Turn raw customer supply-chain data into structured representations and models. Interpret and contextualize noisy data, form and test hypotheses, build inference, regression, simulation and optimization logic, validate model quality in production, and translate scientific requirements into engineering specifications while collaborating with data engineers and supply-chain experts.

Own revenue and product analytics: build KPIs, dashboards, dbt-style data models, run product/usage experiments, partner with GTM, and deliver executive insights to scale revenue operations.

Build and validate predictive and causal inference models from messy healthcare commercial data; translate models into dashboards/scoring systems; partner with marketing, market access, and commercial teams to inform strategy and deploy model-driven decisions.

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.

Develop and apply data science methods (data cleaning, pipelines, exploration, visualization) and predictive models to extract insights from structured and unstructured data. Work with clients to define questions, build algorithms and systems using ML/AI/NLP techniques, and deliver actionable data-driven recommendations.

Build, maintain, and improve decision systems and predictive models; explore internal and external data; design and run in-market experiments; prototype solutions; recommend data-driven strategic changes; implement advanced analytics methods.

Lead design and implementation of AI/ML models, data integration, analysis, and visualization for translational research. Enhance open-source data platforms (Gen3), enforce data governance, mentor junior staff, collaborate with researchers, and translate scientific requirements into production-ready data science solutions.

Perform advanced analytics and predictive modeling to optimize USCIS field operations. Build dashboards, forecast workloads, track KPIs, conduct impact analyses, run deterministic and probabilistic models, support testing cycles, and advise on IT/AI enhancements to improve staffing and operational efficiency.

Perform statistical and operational analyses, assess and improve data quality, use SQL and GIS/geospatial data to support reporting, evaluate program outcomes, build public-facing reporting tools, and coordinate data sharing and communications with stakeholders.

The Senior Data Scientist will engage with business partners to solve problems using data science, lead model development, and mentor others, focusing on supply chain and causal modeling.