Top Data Science Jobs in Los Angeles, CA

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.

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.

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

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 Data Scientist will analyze complex data sets, build models for strategic recommendations, and collaborate with business teams to enhance website personalization and product recommendations.

Lead forecasting, budgeting, and LTV modeling for eCommerce; develop demand and customer-behavior models; validate A/B tests; drive AI/LLM adoption and prototype solutions; translate analyses into executive-ready insights and partner with Finance, Product, and Marketing.

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.

Support forecasting, predictive modeling, and basic machine learning for ticketing, marketing, finance, and operations. Analyze structured and unstructured data, assist with NLP/text analysis, build dashboards and reports, and communicate insights to stakeholders.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Own the full analytics lifecycle: define problems, extract data, build and deploy models, design experiments, and create Power BI dashboards. Track business metrics, apply statistics and AI/LLM tooling, partner with cross-functional teams, and present findings to stakeholders to inform decisions.

Own statistical methodology for mission engineering: design experiments for large-scale simulations, apply Bayesian and regression methods, build scalable Python data pipelines and surrogate models, quantify uncertainty and sensitivity, produce decision-quality visualizations and reports, mentor teams, and support DoD/DARPA/intelligence programs.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.

The Data Scientist II will oversee data management, design study protocols, train staff, lead report development, and manage client activities using project frameworks.

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.

The Data Scientist II will work with sports tracking data to build models and analyses for NHL and NBA organizations, focusing on data transformation and metrics development.

Develop frameworks and tooling to estimate long-term impacts of product changes from short-term experiment outcomes. Build causal inference methods (experimental, econometric, quasi-experimental), evaluate heterogeneous treatment effects, own major estimation problems, and communicate results to technical and non-technical stakeholders to drive better long-term decisions.

Develop and operationalize graph-based analytics for fraud detection and investigative analysis. Build graph models, apply graph algorithms and ML to detect anomalies, support entity resolution, create visualizations and dashboards, and collaborate with investigators and stakeholders to deploy and maintain production solutions.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

The Sr. Football Data Scientist will build, deploy, and refine analytical models for football insights, managing large datasets and collaborating with teams for high-quality analytics solutions.

As a Staff Data Scientist, you'll develop and deploy machine learning models to enhance renter experiences and optimize property partnerships, collaborating across teams to translate data insights into actionable strategies.

As a Data Scientist III, you'll build customer identity systems, develop recommendation models, predictive analytics for customer behavior, and collaborate with ML Ops and Data Engineering.

This role involves leading data science projects, designing technical solutions, implementing machine learning methodologies, and developing data workflows for cybersecurity applications.

The Data Scientist II will develop machine learning algorithms, architect data solutions, and support cybersecurity initiatives by analyzing complex data sets.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.