Top Data Science Jobs

The Experienced Data Scientist will design, develop, and deploy models using statistical and machine learning techniques, conduct data analysis, and collaborate across teams to improve model performance and address business needs.

Analyze large, diverse datasets (claims, hazard, geospatial) and apply advanced data science, ML, and AI to model catastrophe, hazard, exposure, and man-made risks. Evaluate vendor models, develop internal risk views and tools, collaborate with domain experts, and support underwriting decision-making and account-specific risk analyses.

Build and maintain financial data models and scalable reporting systems powering ARR, revenue, billings, and other metrics. Partner with Finance, Accounting, Investor Relations, Engineering, and Data teams to ensure data accuracy across close processes, forecast and analyze performance, and operationalize key financial metrics to support executive decision-making and public company reporting.

Build, validate, and operationalize analytics and dashboards on Azure Databricks for Property & Casualty and Employee Benefits. Collect, cleanse, and integrate insurance data, perform exploratory and statistical analysis, prototype analytics solutions, and communicate insights via visualizations to stakeholders while collaborating with engineers and business teams.

Build, validate, and operationalize analytics, dashboards, and applications on Azure Databricks for Property & Casualty and Employee Benefits. Collect, cleanse, and analyze insurance data, create visualizations, prototype solutions, and collaborate with engineers and stakeholders to drive data-driven decisions and improve data quality.

Design, validate, and productionize analytics and dashboards for property & casualty and employee benefits. Collect, clean, and analyze insurance data, build statistical solutions, prototype analytics, and collaborate with engineers and business stakeholders on Azure Databricks.

Design, build, validate, and operationalize analytics, dashboards, and data products for property & casualty and employee benefits. Clean and integrate insurance data, perform exploratory analysis, prototype models, and collaborate with engineers and business stakeholders to deploy solutions on Azure Databricks.

Lead measurement and experimentation for Waymo growth marketing: design incrementality tests (geo holdouts, switchbacks), build LTV and CAC frameworks, run media mix modeling and deep-dive analyses across channels, audiences, creatives, and geos to optimize acquisition and connect marketing performance to business outcomes.

Build statistical and predictive models to measure and optimize marketing, sales, and customer success impact on pipeline, bookings, ARR, retention, and expansion. Analyze paid media performance and conversion funnels, design experiments and causal measurement, forecast revenue, partner with cross-functional teams to define metrics, and communicate data-driven recommendations to senior leadership while improving measurement methodologies and data quality.

Design and build cloud-based analytical products across the Pharmacy Benefits Management ecosystem. Develop predictive and prescriptive models, perform feature engineering and EDA, collaborate with product, data engineering, and business teams, and modernize legacy systems to support forecasting, pricing, and decision-making.

As part of the Data Science and Analytics team, the Data Scientist will drive data-informed decision making and improve developer productivity by analyzing metrics, conducting causal analyses, and presenting actionable insights to stakeholders.

Lead a 5–8 person Data Science team to develop and operationalize FWA detection models using SAS and Python on multi‑payer healthcare claims. Oversee model development, data pipelines, quality reviews, stakeholder presentations, and collaboration with SMEs and BI developers. Split role ~40% management, 60% hands-on coding/analysis.

Lead a team converting simulation and flight operations data into actionable insights. Design evaluation workflows, automated triage, metrics, pipelines, and statistical methods to quantify performance and detect regressions. Define acceptance criteria for releases and connect operational findings to the engineering roadmap while partnering with engineering, flight operations, and analytics.

Lead end-to-end analytics and AI initiatives to solve complex operational, financial, and clinical problems. Build, validate, and deploy predictive models and scalable analytical solutions; partner with stakeholders, present executive-ready findings, and ensure rigor, explainability, and measurable business impact.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

Lead the data science function for a freight pricing venture: develop and deploy ML models for dynamic pricing, demand forecasting, elasticity, and load acceptance; design pricing experiments; partner with engineering to productionize and monitor models; validate business assumptions and set model governance; translate insights to product, commercial, and executive stakeholders.

The Staff Data Scientist at Coupang Ads will develop monetization strategies, analyze KPIs, manage A/B testing, and deliver actionable insights to maximize revenue and improve product performance.

Provide analytical support in Data Science Division, design analytics solutions, and develop end-to-end analytical lifecycles. Collaborate with diverse teams and present findings to technical and non-technical audiences.

The Data Scientist will develop and deploy ML models, analyze data, optimize AI pipelines, and collaborate with teams to deliver AI solutions. Responsibilities include model fine-tuning, data extraction, and staying updated on AI trends.

As a Data Scientist at GLS, you will design data science solutions, develop predictive models, gather and clean data, and present insights to stakeholders while collaborating with business partners and IT.

Design and run advanced statistical and machine learning analyses on large healthcare datasets to evaluate programs, inform policy, and produce visualizations and reports. Collaborate with clinical, policy, and IT teams, ensure data quality and privacy compliance, mentor junior analysts, and translate findings into actionable recommendations to improve care delivery.

Onsite Data Scientist supporting technical targeting and data exploitation: must manipulate high-volume structured and unstructured datasets, build analytic products, and develop/validate methodologies for large-scale parallel processing across clustered computing environments using ECL/HPCC and languages like Python, R, Pig, Java, C, and SQL. Active TS/SCI with Full Scope Polygraph required.

The Data Scientist will support intelligence operations by applying advanced analytics to complex datasets, develop models, and collaborate with teams to enhance mission delivery.

The Data Scientist role involves analyzing complex datasets, developing models, and communicating findings to stakeholders, supporting mission needs through teamwork and data-driven insights.

The role requires a Data Scientist with strong SQL and analytics experience to analyze business data and provide insights using BI tools and Cosmos.