Top Data Science Jobs in Los Angeles, CA

Apply quantitative analysis, data mining, and statistical modeling to generate actionable product and business insights. Design and track core metrics, build dashboards and visualizations, collaborate with product, engineering, and design teams, and use AI tools and scalable analytical workflows to accelerate decision-making while ensuring methodological rigor and data quality.

As a Product Data Scientist, you will analyze user behavior, drive experimentation, build data tools, and collaborate across teams to influence product strategy and innovation at Whatnot.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

The role involves analyzing fraud and risk data, defining KPIs, collaborating on anti-fraud strategies, and creating tools and dashboards for data accessibility at Whatnot.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

Lead data scientist for Mobile Consumer Create, partnering with product, engineering, and design to set strategy and roadmap. Design and run experiments, analyze user behavior to identify engagement "magic moments," define success metrics and frameworks, and help build strong data foundations for the mobile app.

As a Data Scientist II at Oscar, you'll drive data science projects, develop models, collaborate with cross-functional teams, and ensure quality outputs with minimal oversight.

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.

Design measurement frameworks, build scalable analytics and AI-driven workflows, implement causal and Bayesian models, run experimentation (A/B, incrementality), partner with data engineering, and deliver executive dashboards to optimize growth marketing.

As a Senior Data Scientist, you'll analyze complex data, develop predictive models, and aid decision-making for clients using advanced analytical tools.

Lead data science efforts for Space Force clients: explore, clean, and analyze structured and unstructured data; develop, validate, and deploy predictive AI/ML models; build visualizations and pipelines; guide teammates and translate findings into actionable intelligence. Requires collaboration with engineers and mission stakeholders to deliver mission-focused solutions.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

Design and evaluate causal inference experiments and causal ML models to measure product impact, optimize resource allocation, and inform support operations. Build, deploy, and iterate statistical/ML models, analyze tradeoffs, collaborate cross-functionally, and communicate insights to influence decisions and scale data science capabilities.

Develop and apply causal inference and experimentation methods to measure and optimize marketing impact. Pull and analyze data, create features, design experiments, build end-to-end models, and collaborate with cross-functional teams. Communicate findings, lead internal white papers, and advance measurement science to inform marketing decisions.

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

Customer-facing data scientist advising customers on experiment design, statistical methodology, and experimentation architecture; running and analyzing A/B tests; building scalable experimentation programs; creating repeatable frameworks and technical enablement; partnering with Sales, Solutions Engineering, Product, and Engineering to drive customer success.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

The Data Scientist will build predictive models, drive forecasting, design experiments, and translate findings for stakeholders, optimizing healthcare operations.

Perform statistical analysis, predictive modeling, and data visualization on workforce and training data. Build dashboards, produce ad hoc analyses and decision-support products, advise on data governance/privacy, and collaborate with stakeholders to define metrics, deliverables, and reproducible analytic workflows.

Use statistical and causal inference methods to build, implement, and monitor marketing models (Bayesian MMM, multi-touch attribution), analyze A/B and uplift tests, partner with marketing to test and drive data-informed decisions from large web-product datasets.