Top Hybrid Data Science Jobs

Partner with Product and Engineering to define product metrics, design experiments and causal analyses, build reporting and models, analyze user behavior and segments, and translate insights into product recommendations while establishing Product Data Science practices.

The role involves building the marketing data science function, developing metrics, dashboards, and models to analyze marketing effectiveness, and fostering a data-informed culture.

Lead growth-focused data science initiatives, owning LTV prediction models across countries and channels. Translate business questions into models, analyze large customer and marketing datasets, evaluate acquisition quality, monitor and productionise models with engineering partners, and drive data-informed growth and retention decisions.

Lead product-focused data science work: define and track metrics, design and analyze A/B tests, evaluate model and agent performance across conversations and workflows, perform root-cause analyses, build statistical models and dashboards, and partner with Engineering and ML teams to improve instrumentation and data quality.

Lead and build a data science team to develop production AI across operations and post-sales product experiences. Own roadmap, deploy agentic systems and forecasting, partner with stakeholders, ensure production reliability, evaluation, and business impact, and communicate results to executives.

The Senior Data Solutions Partner acts as a liaison between stakeholders and the Data & Engineering organization, prioritizing analytics, automation, and technology use cases while ensuring alignment and governance throughout project delivery.

As a Data Scientist at Retool, you will analyze customer behavior and business performance, build analytical models, and provide insights to guide strategy across teams.

The Data Science Manager will lead a team to enhance music recommendations through data analysis, storytelling, and innovation, collaborating with senior leaders.

The Senior Data Scientist will develop machine learning systems for fraud prevention using behavioral data, collaborate across teams, and mentor junior scientists.

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.