Top Data Science Jobs in Los Angeles, CA

Leads payer healthcare data science and operations consulting initiatives, using business analytics to improve payer processes and performance. Manages teams, client relationships, project resources, strategic planning, process optimization, quality standards, and operational transformation. Coaches junior staff, promotes innovative technologies, and identifies opportunities to enhance operational excellence and business outcomes.

Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Own product analytics for a healthcare platform by translating business questions into research plans, uncovering insights, modeling feature impacts, defining success criteria, and leading A/B testing. Partner with Product, Data Engineering, Finance, Clinical, and Operations teams to influence roadmap decisions, improve provider experience and quality, and optimize marketplace performance.

Lead the development of statistical and machine learning models for time-series and geospatial data. Build analytic solutions, datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and reports. Evaluate algorithm performance, optimize classifiers, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders to deliver reliable mission-focused software and data capabilities.

Develops statistical and machine learning models for kinematic behavior detection using live, historical, time-series, and geospatial data. Responsibilities include data integration, ETL, feature engineering, forecasting, anomaly detection, algorithm evaluation, simulation, visualization, reporting, documentation, and stakeholder collaboration. The role also contributes to mission-focused software applications, APIs, data workflows, code reviews, troubleshooting, and agile development in a remote-first environment.

Lead statistical and machine learning model development for time-series and geospatial data supporting the FALCON mission. Responsibilities include feature engineering, forecasting, anomaly detection, ETL, dataset creation, algorithm evaluation, simulation, data visualization, reporting, documentation, and stakeholder collaboration. The role also contributes to software applications, APIs, data pipelines, code reviews, troubleshooting, and iterative agile development.

Build predictive failure models, real-time anomaly detection systems, diagnostic tools, and operational dashboards for spacecraft manufacturing, testing, and integration. Apply statistical modeling, causal inference, reliability analysis, and data mining to identify root causes, bottlenecks, quality issues, supplier risks, and process improvements. Develop reproducible Python and SQL analyses that support engineering decisions and mission reliability.

Build predictive models, anomaly detection systems, diagnostic tools, dashboards, and statistical quality-monitoring solutions for spacecraft manufacturing and testing. Analyze telemetry, production, supplier, and reliability data to identify failures, bottlenecks, delays, and root causes. Develop reproducible Python and SQL analyses and communicate actionable findings to engineering and operations stakeholders.

Leads experimentation, causal inference, advanced statistical analysis, machine learning, and scalable data-product development. Partners with product, engineering, and research teams to generate insights, identify opportunities, influence executive decisions, and shape product strategy. Owns cross-functional projects, analytics roadmaps, reporting, stakeholder adoption, and methodological standards while translating complex data into actionable business outcomes.

Product Data Scientist responsible for product data modeling, product and revenue analytics, behavioral analysis, A/B experimentation, and product metric governance. The role partners with Product, Revenue, Engineering, and Analytics Engineering teams to deliver scalable insights and influence decisions. It also contributes to agentic analytics by evaluating AI-generated outputs and improving semantic and prompt layers.

Leads development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Responsibilities include feature engineering, forecasting, anomaly detection, data integration, ETL, visualization, algorithm evaluation, simulation, dataset creation, and stakeholder communication. The role also contributes to mission-focused software applications, APIs, data pipelines, documentation, code reviews, and agile development while requiring an active Top Secret or CBP/DHS suitability clearance.

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.

Leads data engineering for the Sentinel program by developing, deploying, and maintaining production ETL/ELT pipelines from structured and unstructured sources. Oversees analytics data strategy, storage, governance, and quality; partners with stakeholders and visualization specialists; mentors junior engineers; conducts code reviews; and establishes engineering best practices for organization-wide analytics and decision-making.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Supports the U.S. Space Force by analyzing model-based systems engineering data, extracting and transforming structured and semi-structured information, and developing scripts, dashboards, visualizations, reports, and data collection frameworks. The role requires Python, Java, SQL, and dashboarding experience, collaboration with systems engineers, on-site work in El Segundo, and an active TS/SCI clearance with SAP eligibility.

Develops advanced analytics, dashboards, data visualization tools, and automated data solutions supporting operational strategy and execution. Leads data quality initiatives, performance reviews, continuous improvement efforts, and cross-functional analytics projects across program management, engineering, and manufacturing. Translates complex data into actionable insights, coaches stakeholders on data literacy, and supports data-driven decision-making across Southern California facilities.

Develop machine learning, AI, statistical, and predictive models using Snowflake and other data sources. Perform data extraction, cleansing, feature engineering, experimentation, visualization, and quality analysis. Partner with business and technical teams to deliver data products, conversational analytics, and actionable recommendations. Lead discovery sessions, communicate insights to nontechnical audiences, mentor analysts, and support enterprise data science projects.

Support data-driven decision-making by collecting, cleaning, and analyzing structured and unstructured data, performing EDA, assisting in building and validating ML and statistical models, creating visualizations and dashboards, documenting findings, and collaborating with cross-functional teams.

Prototype and validate analytical methods and LLM applications for political, media, and advertising data. Build proof-of-concept tools, datasets, pipelines, and applications, then engineer validated methods toward production. Apply statistical and data science techniques, maintain rigorous software development practices, communicate findings clearly, and collaborate with technical and non-technical stakeholders.

Own the analytical strategy for a digital primary care program by defining KPIs, building dbt data models, maintaining the Snowflake/Fivetran/dbt stack, and delivering analytics, forecasting, revenue modeling, dashboards, and AI-assisted workflows. Translate patient, EHR, clinical, and operational data into actionable insights for product, care delivery, operations, leadership, health systems, and payers.

Serve as Netflix Animation Studios’ founding data scientist, developing measurement frameworks, forecasting and scenario-planning models, dashboards, and data products for slate planning, production efficiency, workforce allocation, and strategic decision-making. Partner with studio leadership, data scientists, analytics engineers, and data engineers to establish data foundations, define metrics, analyze operational drivers, and translate complex findings into actionable recommendations.

Analyze large and complex datasets, build statistical and machine learning models, develop data workflows, enrich datasets, and create analytical solutions for business stakeholders. The role includes writing SQL and Python scripts, optimizing model performance, supporting dashboard development, collaborating with data and BI teams, and documenting models and pipelines. This is a fully remote U.S. position focused on delivering analytics applications through Seek’s cloud platform.

Leads advanced data science and machine learning initiatives for healthcare payment integrity, including fraud, waste, and abuse detection, anomaly identification, predictive modeling, statistical analysis, dashboards, and recovery investigations. Provides technical leadership, mentors analysts, integrates production analytical solutions, collaborates with legal and business stakeholders, and presents findings to leadership. Requires healthcare expertise, advanced SQL and programming skills, and knowledge of claims, billing, reimbursement, and program integrity.