Data Scientist, Safety

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 influence cross-functional partners and executives, and translate data into compelling stories


• Self-starter with a curious mindset and a strong sense of ownership


• Ability to combine business intuition with the application of advanced solutions


• A passion for keeping up with the latest ongoings in Data Science and Machine Learning communities, and an obsession for data quality


• Prior experience in Trust & Safety, or Platform Integrity domains is a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits


• Mental health benefits


• Family building benefits


• Child care and pet benefits


• Access to a Lyft funded Health Care Savings Account


• RRSP plan with company match to help save for your future


• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 


• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.


• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108000-$135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.