Top Hybrid Data Science Jobs

Lead end-to-end data science for lending products: define metrics, run experiments, build measurement systems, evaluate model and policy performance, use AI tools to accelerate analysis, and mentor the team while partnering with product, engineering, and risk stakeholders to drive credit product decisions.

Partner with Marketing to own attribution, ROI, conversion, and funnel analysis. Design experiments, surface proactive insights, optimize marketing spend, and collaborate with Data/Analytics Engineers to build data models and pipelines. Communicate findings and recommendations to non-technical stakeholders.

Lead analytics strategy and decision support, perform deep-dive analyses, build predictive and ML models, design experiments, create trusted reporting and dashboards, ensure data quality, partner cross-functionally, and influence product, growth, revenue, operations, and finance through evidence-based recommendations.

Lead Chewy Ads Data Science across onsite and offsite channels, owning strategy, roadmap, models, and experimentation. Build and mentor a team to deliver production ML systems for ranking, bidding, budget optimization, ROAS, and GenAI-powered advertiser tooling while partnering with Product and Engineering and representing science to senior leadership.

Perform data cleaning, preprocessing, integration, and quality assurance; create complex visualizations and dashboards (Tableau/Power BI); run routine data quality checks; and apply AI/ML models to analyze unstructured data to support mission-critical decision making.

Lead data science initiatives across core business domains: collaborate with stakeholders and engineers, analyze large datasets, design experiments, build and productionize statistical and ML models, harden pipelines, monitor performance, and mentor teams to drive data-informed decisions.

As a Data Scientist, you'll develop and validate machine learning models, implement AI solutions, and conduct fieldwork in support of customers.

Data Science Interns will collaborate with product and engineering teams to translate business questions into data problems, evaluate experiments, develop behavioral and growth models, and build scalable data pipelines and tools. Projects may focus on analytics, experimentation, infrastructure, user behavior, KPI research, and funnel analysis. Strong coding, statistics or data systems knowledge, communication, and problem-solving skills are expected.

Leads advanced data science and machine learning initiatives addressing complex business challenges. Develops predictive models, analytical strategies, and data visualizations to drive business decisions. Partners with cross-functional teams to create scalable data solutions, maintain data quality and governance, and translate requirements into measurable outcomes. Mentors data science professionals and advances analytics best practices across Walmart’s Marketplace Engineering organization.

Analyze structured and unstructured data, develop and test statistical/analytical models, prepare and validate data, partner with engineers and product teams to build end-to-end analytical solutions, evaluate new data sources and methods, document approaches, and communicate findings to stakeholders.