Data Scientist, Safety

Job Description

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety & Customer Care (SCC) organization manages over 1.7 million monthly customer interactions and is responsible for ensuring the trust and safety of our riders and drivers. We work every day to build a trusted community, foster safe interactions, manage risky situations, and deliver best-in-class support. As part of this team, you will play a critical role in making transportation safer for all. We are looking for an experienced and highly motivated Data Scientist to join the Community Safety Data team and lead key initiatives that enhance the safety of Lyft’s community. You’ll work cross-functionally with product management, engineering, design, legal, research, and operations teams to build impactful safety features, models, and systems. This high-impact role requires deep customer empathy, insatiable curiosity to uncover platform risks; and competencies to explore large datasets, develop statistical models, and design data-driven strategies for products that provide safe and engaging experiences for customers. You’ll report to the Director of Data Science for the SCC org. Responsibilities: Leverage data and analytical frameworks to identify opportunities for improving community trust and safety Partner with product managers, engineers, designers, marketers, and operators to translate insights into scalable, safety-forward decisions Design and analyze online experiments; interpret and communicate results to influence product launch decisions Build and monitor key metrics that reflect rider and driver safety, product health, and policy compliance Develop rigorous measurement strategies to evaluate the effectiveness of safety features, interventions, and detection systems Drive proactive risk identification and continuous improvement through analysis, experimentation, and iteration Mentored junior data scientists by providing guidance, feedback, and support to accelerate their technical and soft skill growth and impact. Experience: Degree in a quantitative field such as Statistics, Economics, Applied Mathematics, Operations Research, or Engineering (advanced degrees preferred), or equivalent professional experience 3+ years of industry experience in data science or product analytics roles Proficiency in SQL with ability to write efficient queries on large, complex datasets Experience programming in Python or R, especially for data analysis, visualization, and modeling Strong foundation in statistical analysis and experimentation, including A/B testing design and/or Causal Inference techniques Excellent written and verbal communication skills with ability to influen

Required Skills