Top Hybrid Data Science Jobs

Lead development and deployment of predictive, risk-scoring, and optimization models for behavioral health using claims and clinical data. Define data science infrastructure, perform deep analytics, translate models into client-facing impact and dashboards, and lead cross-functional product and client engagements.

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.

Lead product-focused data science at OpenArt: design experiments, build metrics and dashboards, run user and behavioral analyses, inform product and growth decisions, collaborate cross-functionally, and establish DS best practices as the first US hire.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Data Scientist II estimates, develops, and implements consumer credit models related to mortgage metrics and utilizes statistical methods and machine learning. This role involves cloud computing, data analysis, and communication of findings to nontechnical teams.

Lead data and reporting infrastructure for portfolio companies, perform ad-hoc analysis and predictive modeling, build reusable IP, conduct portfolio-level marketing/sales/customer success analysis, and evaluate/implement AI tools across the firm and its portfolio.

Own the analytics lifecycle: build SQL/Python analyses and ETL, define metrics and reusable data models, produce customer-facing ThoughtSpot dashboards and ROI analyses, prototype ML solutions, improve data quality, and design and maintain the analytics data warehouse and pipelines.

Lead forecasting, budgeting, and advanced analytics for eCommerce; build and maintain LTV and demand-forecasting models; validate A/B tests; drive AI/LLM strategy and prototypes; partner cross-functionally with Finance, Marketing, Product, and Data Engineering; translate analyses into executive-level storytelling and decision support.

Lead design, execution, and analysis of A/B tests across underwriting and product. Define core product and financial metrics, translate model outputs into business decisions, build forecasting frameworks, and advise Product, Finance, Risk, and Engineering to balance growth, risk, and unit economics.

Work with media strategists, data scientists, and engineers to design and execute campaign measurement, experimentation, and optimization. Manage projects, ingest and clean data, perform statistical analyses, build reproducible Python/SQL solutions, create client-facing reports and dashboards, and help productionalize tools to improve media performance and business outcomes.