Data Scientist, Decisions - Mapping

As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including:

• How do we improve the quality of our map data in order to improve our recommendations?
• How do we benchmark and measure the success of our services?
• How do we validate features of the real world that affect our routing algorithms?
• Are we meeting our travel estimation promises to our customers?

Responsibilities:

• Leverage data and analytic frameworks to identify opportunities for growth and efficiency
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
• Design and analyze online experiments; communicate results and act on launch decisions
• Develop analytical frameworks to monitor business and product performance
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Identify and drive impact and alignment, shaping product and business strategy through data-centric presentations

Experiences:

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 1+ years experience in a data science role or analytics role
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Experience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, Keras
• Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
• Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners
• Experience in applying machine learning techniques a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
• Experience working with ETL pipelines 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

The expected base pay range for this position in the Toronto area is CAD $88,000 - CAD $110,000, 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.

This job fills an existing vacancy.