Top Entry Level Data Science Jobs in San Diego, CA

Develops scalable data and analytics solutions for BILL’s compliance ecosystem. Responsibilities include extracting and analyzing data, building dashboards, maintaining compliance metrics, automating workflows, troubleshooting systems, performing root-cause analysis, and supporting technology accelerators. The role requires SQL, Python, Excel, business intelligence tools, and experience with risk or compliance systems in payments or financial services.

Analyze large datasets, identify meaningful patterns, develop machine learning models, and deliver actionable insights for business decisions. Collaborate with cross-functional teams to understand data needs, communicate findings clearly to stakeholders, and stay current with advances in data science and AI technologies.

Assist senior data scientists with data collection, preprocessing, cleaning, and basic statistical analysis. Support model development, perform basic visualizations, and document processes and findings while learning and applying data science techniques.

Own end-to-end data science for emerging content surfaces, including product experimentation, causal inference, exploratory analysis, metrics, dashboards, and strategic insights. Identify opportunities to grow content supply, creators, and engagement while improving discovery. Lead content data architecture and quality initiatives, develop source-of-truth assets, and apply advanced statistical methods such as quasi-experiments and network testing. Partner with Product, Engineering, Design, and Research to influence product direction and communicate findings to diverse audiences.

Develop and deploy machine learning models, design experiments and A/B tests, productionalize data science code with GitHub and MLOps pipelines, and collaborate with data vendors. The role offers hands-on experience with cloud infrastructure, advanced machine learning tools, and production AI systems while working alongside senior engineering and data science leaders.

Analyze credit strategies and lending performance using SQL queries, complex data aggregations, and quantitative methods. Evaluate credit policy changes, monitor portfolios, identify business improvement opportunities, and present data-backed recommendations to Risk, Operations, and other stakeholders. Collaborate with data vendors and senior leaders to support AI-driven lending and strategic decision-making.

Partner with product engineering to design and analyze experiments, apply causal reasoning and statistical modeling to marketplace data, and drive data-informed product decisions across the engineering org.