Top Senior Data Science Jobs in Los Angeles, CA

The role involves managing AI/GenAI solution development, analyzing client needs, mentoring team members, and overseeing project execution.

The Staff Data Scientist will build AI systems, lead model development and analysis, ensure quality of AI solutions, and collaborate effectively with teams.

The Staff Data Scientist will lead projects to drive insights, define business metrics, advance experimentation, and collaborate with various teams to enhance user experience and product performance.

The role involves developing advanced predictive models, managing project timelines, collaborating with engineering teams, and ensuring model alignment with business needs.

The Staff Data Scientist will build and manage machine learning models to optimize personalization, inventory, and logistics while leading the ML function and collaborating cross-functionally.

The Data Scientist will develop and deploy scalable ML models utilizing NLP to enhance security solutions, collaborating with cross-functional teams.

Responsible for analyzing crypto-related data, mentoring a data team, and collaborating on blockchain research to enhance Circle's products and security.

As a Senior Staff Data Scientist, you'll define data strategy, mentor team members, advance experimentation practices, and collaborate with various teams to enhance product and business metrics.

The Data Scientist will analyze data, develop models, collaborate across teams, and support strategic projects to drive insights and growth.

The role involves analyzing user behavior to prevent account sharing, developing predictive models, collaborating with teams, and ensuring data privacy compliance.

Build and improve ad-serving products, develop custom data science solutions, apply advanced techniques in machine learning, and conduct scientific analysis.

The Senior Data Scientist will evaluate monetization impacts, engage in product analytics, A/B testing, and partner with teams to drive data-informed strategies.

The Lead Data Scientist will drive statistical methods for autonomous vehicle safety metrics, develop data solutions, and enhance safety assessments while collaborating with various teams.

The Senior Data Scientist will optimize product performance through data analysis, collaborate with teams to provide insights, and support product initiatives.

As a Staff Data Scientist, lead high-impact data science projects, mentor team members, and innovate using AI and machine learning. Collaborate across teams to enhance products and deliver insights.

The Data Scientist will perform research on DeFi protocols, manage client engagements, and create dashboards while analyzing complex datasets.

Design and implement predictive models using machine learning for underwriting and patient care. Analyze healthcare data to inform strategies and collaborate with cross-functional teams.

As a Senior Data Scientist at Gradient AI, you'll design predictive models for insurance underwriting, analyze large datasets, and collaborate with cross-functional teams.

The Senior Data Scientist will develop predictive models, analyze large datasets, and collaborate with teams to enhance machine learning services at Crunchyroll.

Analyze datasets using SQL and Python, evaluate experiments, partner with ML engineers for model development, and communicate insights to stakeholders.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Senior Data Scientist will drive product innovation through experimentation and robust measurement strategies in Netflix Games, collaborating with Product and Engineering teams to enhance user experience.

The role involves designing forecasting models for revenue, collaborating with teams to optimize growth strategies and drive analytics for business decision-making.

The role involves leading data science initiatives to drive business outcomes, mentoring junior scientists, performing analyses for decision-making, and using advanced technologies for optimization and causal analyses.

Conduct analyses on ambiguous problems, guide data ownership, and maintain statistical rigor while influencing stakeholders through data storytelling.