Data Scientist, Payments & Fraud Integrity

Lyft; Toronto; Hybrid; CAD 108,000 - 135,000; Full time

Benefits offered by this job

Extended health coverage

Mental health benefits

Family building benefits

RRSP match

Paid time off policy

Job summary

Lyft is seeking a Data Scientist for the Pay, Integrity & Identity org in Toronto. You will run experiments, build ML models, and analyze signals to prevent fraud while maintaining a positive rider and driver experience.

Ideal candidates have 4–6 years in data science, strong SQL, and Python or R skills, plus clear communication to cross-functional partners. This role is hybrid, with in-office presence required several days a week in Toronto.

Qualifications

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred) or relevant work experience.
• 4–6 years of industry experience in a data science or analytical role.
• Proficiency in SQL with ability to write structured queries on large data sets.
• Experience in Python or R for data science and visualization.
• Strong written and oral communication; collaboration across cross-functional teams.

Responsibilities

• Design and analyze experiments in collaboration with scientists, product and engineering; communicate findings to stakeholders.
• Leverage advanced statistical techniques to generate insights and develop ML models.
• Analyze signals to identify patterns in large datasets and root causes.
• Partner with product managers and engineers to translate insights into decisions and actions.
• Build data pipelines and analytical frameworks to monitor performance.
• Set business metrics to measure product health and user experience.

Skills

SQL

Python/R

Communication

Education

Degree in quantitative field or relevant work experience

Job description

Lyft is seeking a Data Scientist for the Pay, Integrity & Identity org in Toronto. You will run experiments, build ML models, and analyze signals to prevent fraud while maintaining a positive rider and driver experience.

Ideal candidates have 4–6 years in data science, strong SQL, and Python or R skills, plus clear communication to cross-functional partners. This role is hybrid, with in-office presence required several days a week in Toronto.