Data Scientist, Decisions - Payments at Lyft

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.

As a Data Scientist in the Pay, Integrity & Identity org, you will collaborate with our world class team of engineers, product managers, analysts and other data scientists to help create best in class pay platforms, stop fraudulent actors from harming our riders & drivers fraud and build user trust on the Lyft platform. You will run experiments (A/B tests) and develop data driven solutions to launch new features and remove the bad actors from the Lyft platform while maintaining a positive experience for genuine users. We’re looking for an intellectually curious individual who has extraordinary attention to detail, a track record of analytical problem-solving and skilled communication.

Prior experience in the fintech, fraud or identity space is preferred.

Responsibilities:

• Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions
• Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models
• Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action
• Build data pipelines and develop analytical frameworks to monitor business and product performance
• Set business metrics that measure the health of our products, as well as passenger and driver experience
• Collaborate with product and engineering and communicate findings to stakeholders in a clear and concise manner

Experience:

• 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 - able to write structured and efficient queries on large data sets
• Experience in programming, especially with data science and visualization libraries in Python or R
• Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• 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 pe

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