Data Scientist - Decisions, Mapping
Lyft View all jobs
- Toronto, ON
- $108,000-135,000 per year
- Permanent
- Full-time
- 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?
- 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
- Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
- Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope
- Design and analyze online experiments; communicate results and act on launch decisions
- 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
- Contribute to the Science community (hiring, onboarding, documentation, knowledge-sharing, tooling improvements), helping make Decision Science at Lyft more effective and scalable
- Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
- 3+ years experience in a data science role or analytics role
- Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration
- End-to-end experience with data, including querying, aggregation, analysis, and visualization
- 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, 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 communication, critical thinking, and prioritization skills, including the ability to challenge assumptions, propose alternatives, and balance short-term vs. long-term tradeoffs
- Experience in applying machine learning techniques is a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
- Expertise in metric design, causal analysis, behavioral analytics, decision frameworks and measurement strategy is a plus
- Experience working with ETL pipelines a plus
- 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