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.

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.

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

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.

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.

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.

The role involves deploying data science solutions in cybersecurity, collaborating with customers and teams to operationalize models and enhance security insights.

Lead data-driven strategy by partnering with senior executives to deliver rigorous analytical solutions. Design and implement sophisticated analyses on large-scale data, build trusted cross-functional relationships, mentor data scientists, and influence long-term product and business decisions.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

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.

Build and maintain large commercial datasets and predictive/forecasting models (BigQuery, dbt, SQL, Python). Design causal and experimental analyses to measure promotion impact and price elasticity. Partner with commercial, finance, and executive stakeholders to inform pricing, distribution, and investment. Deploy LLMs and AI agents to classify unstructured data and build tools that democratize data access.

The role involves developing graph algorithms, data pipelines for identity verification, and supporting data analysis for compliance products.

Design, validate, and deploy scalable statistical and distributional models for enterprise consumer analytics. Implement rigorous methodologies, convert ad-hoc analyses into version-controlled analytical libraries, and partner with Data Engineering to optimize performance and scale compute workloads (including cloud/Databricks). Deliver reproducible analytics powering dashboards and LLM-driven applications, with a focus on panel and transaction-level consumer data.

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.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

Embed within GTM Marketing to design experiments, build attribution, propensity, churn, segmentation, and conversion models; analyze product engagement and organic search signals; partner with analytics engineers to productionize models; and translate statistical results into actionable business recommendations.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

As a Data Scientist, you will develop predictive models, analyze geoscientific data, and collaborate with geoscientists to improve mineral exploration efforts.

The Data Scientist role involves designing and deploying machine learning systems, prototyping AI agents, collaborating with product teams, and addressing business problems. Responsibilities include model building, data analysis, client collaboration, and contributing to AI tooling.