Top Data Science Jobs

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.

Lead advanced analytics and predictive modeling to optimize marketing channels. Design, develop, and deploy complex models and algorithms, test hypotheses, communicate insights to senior leaders, mentor team members, and drive best practices in model lifecycle and ethical AI.

Lead design and scaling of yield, pricing, and matching models; analyse large-scale trading and behavioral data; define data science strategy for optimisation and forecasting; partner with commercial, engineering and product teams; mentor senior/mid-level data scientists; communicate technical findings to non-technical stakeholders and ensure robust production deployment.

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.

Lead end-to-end data science initiatives across pricing, dispatch, ETA, routing, and forecasting. Turn ambiguous logistics problems into production ML solutions, build data pipelines, partner with engineering to deploy models, establish evaluation and A/B testing, and work directly with customers and leadership to measure business impact.

As a Lead Data Scientist at Oliver Wyman, you will manage analytics projects, develop models, and engage with global clients to solve business challenges using advanced data science methodologies.

The Senior Data Scientist will manage and deliver analytics projects, engaging with clients to solve business problems using data science and machine learning techniques.

Analyze large-scale mobile user and app datasets to inform product and ML strategies, collaborate cross-functionally, build dashboards and processes, and present statistical analyses to improve platform performance.

Own statistical methodology for mission engineering: design experiments for large-scale simulations, apply Bayesian and regression methods, build scalable Python data pipelines and surrogate models, quantify uncertainty and sensitivity, produce decision-quality visualizations and reports, mentor teams, and support DoD/DARPA/intelligence programs.

Lead and execute complex analyses of large-scale health care claims, build data pipelines and analytic infrastructure, ensure data quality and reproducibility, manage projects and timelines, mentor junior staff, and translate results into policy-relevant insights.

The Senior Data Scientist will develop and deploy machine learning models for yield optimization, pricing, and inventory allocation in programmatic advertising. Responsibilities include building data pipelines, real-time inference systems, conducting experiments, and collaborating with product and engineering teams to enhance marketplace performance.

The Senior Data Scientist will design and deploy ML models for yield optimization and inventory allocation in programmatic advertising, build data pipelines, and monitor performance for effective marketplace balance.

Senior individual-contributor owning product and growth analytics: define and measure funnel metrics (signup, activation, conversion, retention), design and analyze experiments, build predictive models (activation, churn, LTV), clean and warehouse product/billing events, create dashboards and writeups, and partner with growth, product, and founders to find and size high-leverage opportunities.

The Data Scientist will design and develop advanced analytics applications, employing machine learning and statistical techniques to interpret complex datasets and improve operational effectiveness.

The Data Scientist SME will develop and scale GEOINT AI/ML pipelines, design ML models for geospatial datasets, mentor teams, and operationalize analytics in a cloud environment.