Top Data Science Jobs

Own the end-to-end analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to influence decisions and drive measurable outcomes. The role requires strong analytical ability, independent problem-solving, clear communication, and ownership of ambiguous initiatives.

Own the analytical function for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to communicate findings, influence decisions, and drive measurable outcomes. The role requires strong analytical problem-solving, independent execution, and persuasive communication.

Develops predictive and prescriptive models using statistical, machine-learning, deep-learning, and generative AI methods. Consults with business users, oversees data science applications and proof-of-concepts, ensures analytical integrity and regulatory compliance, creates KPIs and reports, and mentors junior team members. The role collaborates cross-functionally with senior Operations leaders and supports quality, product, and process analytics in a pharmaceutical environment.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, pull and structure data, build reports, run analyses, design experiments, communicate insights, and drive recommendations and decisions with cross-functional stakeholders. Requires strong analytical thinking, independent execution, persuasive communication, and experience solving ambiguous problems in consulting, investment banking, or high-growth technology.

Own end-to-end data science for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires independent analytical execution, first-principles problem solving, persuasive communication, and ownership of ambiguous initiatives that drive measurable business outcomes.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate insights; and drive decisions and measurable outcomes with cross-functional stakeholders. The role requires independent data work, strong problem-solving, persuasive communication, and ownership of ambiguous initiatives from end to end.

Own end-to-end data science for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate actionable insights; communicate recommendations; and drive decisions and measurable outcomes with cross-functional stakeholders.

Develop and deploy predictive models, machine learning algorithms, and advanced analytics for Department of Defense missions. Responsibilities include data exploration, feature engineering, statistical analysis, model deployment and monitoring in secure environments, analytical visualization, stakeholder collaboration, and mentoring junior data scientists. The role requires an active TS/SCI clearance and experience with Python or R, AI/ML techniques, data governance, and federal compliance.

This role involves analyzing EHR and insurance claims data to define clinical outcomes, developing AI models, and collaborating with technical experts for manuscript preparation.

Collects, cleans, transforms, explores, and statistically analyzes clinical, financial, and operational data. Builds visualizations and dashboards using tools such as Power BI and Tableau, communicates findings and recommendations to stakeholders, and collaborates with domain experts to evaluate program effectiveness. The role requires healthcare or pharmacy experience, SQL programming, strong analytical skills, attention to detail, and compliance with data privacy regulations such as HIPAA.

Develop data science, analytics, data engineering, and AI/ML solutions for Federal clients using Python, SQL, cloud platforms, Databricks, LLMs, and visualization tools. Build data pipelines, wrangle data, deploy models, automate processes, communicate insights, gather client requirements, and support business development efforts. An active Secret clearance and at least three years of experience are required.

Develop and maintain data pipelines, models, dashboards, visualizations, and analytical tools for research and decision-making. Use SQL and Python to integrate, clean, transform, and validate data, including spatial datasets. Create Power BI semantic models and GIS visualizations, translate stakeholder needs into technical solutions, document workflows, support data governance, and troubleshoot data products. Apply statistical analysis, machine learning, data mining, and reproducible research methods to answer research questions.

Lead and validate the firm's physical-risk signal through rigorous backtests, statistical modeling, and hypothesis-driven research. Translate hazard exposure into asset-level earnings impact, define methodology and assumptions, and guide product roadmap based on where the signal is strong or weak. Deliver end-to-end analyses, collaborate with founders, and communicate methods to stakeholders and buy-side partners.

Develops and oversees predictive and prescriptive models using statistical, machine-learning, deep-learning, and generative AI methods within Operations Quality. Consults with business users, delivers data science applications and proofs of concept, ensures analytical integrity and regulatory compliance, and supports KPIs, reporting, and statistical analyses. The role collaborates with senior leaders and cross-functional teams while mentoring junior data science staff and managing multiple priorities.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

Develop predictive models, algorithms, and quantitative analyses using structured and unstructured data. Explore, clean, analyze, mine, and visualize data to solve client problems across public and private sectors. Apply machine learning, natural language processing, and text-mining techniques, lead complex solution development, guide teammates, and translate findings into actionable recommendations. Collaborate directly with clients and leverage modern data science tools and distributed computing frameworks.

Develop frameworks and tooling to estimate long-term impacts of product changes from short-term experiment outcomes. Build causal inference methods (experimental, econometric, quasi-experimental), evaluate heterogeneous treatment effects, own major estimation problems, and communicate results to technical and non-technical stakeholders to drive better long-term decisions.

End-to-end data scientist who analyzes messy SEO/AEO data, designs and runs experiments, implements fixes using internal tooling, ships improvements, and communicates decision-ready reports to clients while improving tools and processes.

Lead forecasting, budgeting, LTV and retention modeling, and advanced analytics for eCommerce. Drive AI/LLM adoption, build prototypes and scalable solutions, validate A/B tests, partner cross-functionally, and translate analyses into executive-level narratives to inform strategic decisions.

Analyze and interpret survey and operational datasets to produce statistical analyses, visualizations, and actionable insights. Develop, maintain, and enhance tools, databases, and processes for survey creation and exploitation. Ensure data quality across multiple sources and constrained environments, document methodologies and SOPs, provide customer support, and collaborate with mission partners to improve survey workflows and enable informed decision-making.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

As a Data Scientist Level 3, you will apply data science expertise to national security challenges, develop analytical tools, and communicate insights effectively to diverse audiences.

As a Data Scientist, Level 3, you'll leverage Python to automate workflows, perform data manipulation, and create visualizations, applying advanced analytics to complex datasets and communicating insights to varied audiences.

As a Data Scientist in the Innovation Team, you'll develop machine learning algorithms on molecular sequencing data to enhance cancer diagnostics and treatment, collaborating with diverse experts on high-impact projects.

The data scientist will optimize credit and marketplace products using machine learning, create algorithms, analyze experiments, and manage ML infrastructure.