Top Senior Data Science Jobs in Los Angeles, CA

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

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.

Develop and maintain predictive pricing, retention, and conversion models using GLMs and advanced analytics; build monitoring tools for rating performance; support rate filings, product pricing analyses, competitor research, and cross-functional collaboration to inform pricing and enterprise risk decisions.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

Lead research and experimentation to measure ad campaign performance and effectiveness. Design evaluation frameworks, build measurement solutions, develop models for lift, conversion, and attribution, run experiments and analyses, partner with product/engineering/design/sales, present insights, mentor teammates, and foster technical community and culture.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Design and deploy predictive forecasting and analytics to support Revenue operations. Build models for forecasting, churn, expansion, and pipeline analytics; create scalable dashboards; partner with Revenue Operations, Finance, and Data Engineering to improve data quality, KPI governance, and executive reporting to drive data-driven decisions and AI readiness.

Activate and operationalize clinical data for analytics by designing data models, taxonomies, and a clinical feature store; build reusable data assets, documentation, and dashboards; ensure data quality and compliance; partner with stakeholders and data engineering to enable downstream analysts, data scientists, and business users.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Lead marketplace measurement, experimentation, and causal analysis; build pricing, recommendation, and retention models; operationalize models with engineering; maintain dashboards and monitor supply-demand balance to guide product and growth decisions.

Lead end-to-end on-chain data ingestion, attribution, and composability decoding for DeFi surveillance. Build and integrate wallet-clustering feeds, trace funds across chains and bridges, co-develop optimistic-oracle (UMA) surveillance R&D, and deliver versioned on-chain feature tables for detection and validation systems.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

Consult as a fractional data scientist for hedge funds, private equity firms, and family offices. Lead data science initiatives: build infrastructure, develop and deploy models, create portfolio dashboards, monitor post-deployment performance, and partner with investment teams to turn data into actionable investment insights. Advise on vendor selection, data quality, technology stacks, KPIs, and governance.

Lead data-science projects with customers to acquire and prepare data, develop and evaluate production-scale models, drive model best practices, contribute thought leadership and open-source solutions, and define business and solution strategy while collaborating across engineering teams.

Lead the data science function for a freight pricing venture: develop and deploy ML models for dynamic pricing, demand forecasting, elasticity, and load acceptance; design pricing experiments; partner with engineering to productionize and monitor models; validate business assumptions and set model governance; translate insights to product, commercial, and executive stakeholders.

Lead product analytics for Roku's Home screen and discovery features: analyze structured and unstructured data, build dashboards and data pipelines, design A/B tests and models, provide actionable insights to product and engineering, and advise leadership to drive adoption and business value.

Hands-on senior data scientist splitting work between SQL Server data engineering (ETL, pipeline modernization, data quality) and analytics delivery (Power BI semantic models, dashboards, statistical and predictive modeling). Duties include designing migration options, implementing Python-based cleansing and reproducible analytics, building ETL/deployment processes, responding to ad hoc leadership data requests, and documenting systems for stakeholders. Must obtain VA background/PIV and be a U.S. citizen.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

The role involves building and validating Marketing Mix Models and geo-experiments, managing measurement infrastructure, and communicating insights to stakeholders.

Lead product and program analytics for Microsoft skilling experiences: design learner journey/funnel analyses, define success metrics, run experiments and causal analyses, build proficiency/competency models, shape telemetry and scalable reporting, recommend content and curriculum improvements, and mentor other data scientists to drive product decisions and learning outcomes.

Lead product and program analytics for Microsoft skilling experiences. Design funnel and learner-journey analyses, define success metrics, build measurement frameworks, run experiments and causal analyses, develop competency/skill models, partner with product and engineering on telemetry, recommend content and curriculum improvements, mentor data scientists, and ensure data privacy and telemetry quality.