Top Hybrid Data Science Jobs

Lead people analytics by building dashboards and predictive models across the employee lifecycle. Apply advanced statistical methods, NLP/GenAI, and survival/forecasting analyses to surface insights on attrition, skills gaps, performance, and org health. Drive data governance, ensure privacy/PII controls, enable self-service analytics, and partner with HR, TA, Finance, IT, and senior leaders to inform workforce planning and strategic decisions.

Undergraduate intern will run experiments and evaluations for AI-for-science projects, assist with data cleaning and analysis, document findings, and present a technical report under mentorship of the Data Analytics and Insights team.

Partner with clients to define data science strategies, conduct analyses, create roadmaps and business cases, communicate methods to non-technical audiences, collaborate on end-to-end solutions, and identify/deploy ML and GenAI solutions.

As a Founding Data Scientist, you will develop predictive models and optimize data infrastructure to enhance supply chain operations, focusing on shipment risk and decision-making.

The Data Scientist III will enhance cybersecurity operations using data science and machine learning techniques, developing analytical models, and integrating data from various sources to improve threat detection and monitoring.

The Data Science Engineer will develop and apply machine learning and data science algorithms for cybersecurity and power systems, designing solutions and collaborating with multidisciplinary teams to enhance critical infrastructure resilience.

Lead growth-focused data science to accelerate user adoption, engagement, and retention. Define measurement frameworks, build funnels and reusable datasets, design and analyze experiments using causal inference, develop behavioral segments, and partner cross-functionally to translate insights into product decisions and roadmap priorities.

Lead analytical projects end-to-end to inform product, marketing, and commercial strategy. Build segmentation and predictive models (churn, LTV, propensity), design and analyze experiments, apply causal inference, and build AI/agentic workflows to operationalize decisions. Communicate findings to leadership and partners, collaborate cross-functionally, and contribute to team practices through code reviews and knowledge sharing.

The Data Scientist will build AI-driven fraud and risk systems, work with real-world data, and leverage graph techniques to improve detection and labeling. They will partner with engineering to scale data systems in the compliance domain.

The Staff Data Scientist will lead data science projects, build ML models, develop AI solutions, and mentor junior staff while integrating data-driven insights into business operations.