Data Scientist, Decisions - Payments
Toronto, Canada
- Pay
CAD 108,000–135,000/year · BaseAnnual period assumed — pay source
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 $108,000-$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.
Read the full posting- Work setting
Hybrid stated — work setting source
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 $108,000-$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.
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingDesign and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions
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
From the employer’s posting
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
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
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
What you’ll bring
All qualificationsCore 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
Qualification wording
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
Tools in this posting
- Python
- R
- SQL
Source — Tool mentions in context
- 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
- 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
Benefits in the posting
Full benefits wording- 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 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
- The expected base pay range for this position in the Toronto area is CAD $108,000-$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.
From the employer’s posting.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 22, 2026 · 3 days ago
- Recorded sightings
- 13
- Last seen by us
- Oct 25, 2026
- Reposted
- once since Aug 5, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
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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.
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 build best-in-class payment experiences for Lyft drivers. Your work will sit at the intersection of financial systems and driver experience, ensuring drivers are paid accurately, quickly, and fairly, while protecting the integrity of Lyft's pay platform. You will run experiments (A/B tests) and develop data-driven solutions to launch new payout features, improve earnings transparency, and maintain a trustworthy platform experience for the driver community. 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
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- RRSP plan 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
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 $108,000-$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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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 $108,000-$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.
- Location & working pattern
Toronto, Canada
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- Work authorization
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