About this role
Improving map data quality and travel time estimation accuracy requires sophisticated analysis to help rideshare drivers navigate safely and efficiently. The Mapping team at Lyft addresses this challenge by relying on rigorous analytical thinking to shape routing algorithms and measure service success.
As a Data Scientist on this team, you will scope opportunities, design experiments, and collaborate closely with engineers and product managers. You will handle spatial data, build metrics to monitor product performance, and translate analytical insights into actionable business decisions.
Success in this role suits someone who combines technical proficiency in SQL and Python with strong cross-functional communication skills. Candidates who enjoy solving complex spatial problems and connecting analytical frameworks directly to product strategy will find a strong fit here.
What you will do
- Leverage data and analytic frameworks to identify opportunities for growth and operational efficiency.
- Partner with product managers, engineers, and operators to translate analytical insights into decisions, action, and new product implementations.
- Design and analyze online experiments, communicate results clearly, and act on launch decisions.
- Develop analytical frameworks to monitor overall business and product performance.
- Establish metrics that measure the health of products as well as the rider and driver experience.
- Identify and drive impact and alignment to shape product and business strategy through data-centric presentations.
What you need
- Hold a degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering, or possess relevant work experience.
- Bring at least one year of professional experience in a data science or analytics role.
- Demonstrate proficiency in SQL with the ability to write structured and efficient queries on large data sets.
- Possess end-to-end data experience encompassing querying, aggregation, analysis, and visualization.
- Show programming experience in Python or R using data science, visualization, and machine learning libraries.
- Bring experience in online experimentation, statistical analysis, and communicating recommendations to senior stakeholders.
Nice to have
- Advanced degrees in a quantitative field
- Experience applying machine learning techniques like reinforcement learning to solve customer problems
- Experience working with ETL pipelines
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 and an RRSP plan with company match
- Flexible paid time off policy for salaried team members
- 18 weeks of paid time off for new parents as a top-up plan
- Subsidized commuter benefits and Lyft ride credits
Skills and tech stack
Questions candidates ask
What is the remote or in-office policy for this role?
This role operates on a hybrid schedule requiring team members to work in the office at least 3 days per week, specifically on Mondays, Wednesdays, and Thursdays. Additionally, hybrid roles include the flexibility to work from anywhere for up to 4 weeks per year.
What is the expected salary range for this position?
The expected base pay range for this position in the Toronto area is CAD $88,000 to CAD $110,000. This range does not include potential equity offerings, bonuses, or benefits, and varies based on qualifications, experience, and geographic location.
What qualifications are needed to apply?
Applicants need a degree in a quantitative field or relevant work experience, along with at least one year of experience in a data science or analytics role. Candidates must also demonstrate proficiency in SQL, end-to-end data handling, and programming in Python or R.