Data Scientist, Optimization - Real-Time Supply Management
Design and deploy optimization algorithms and incentive systems that improve driver engagement, marketplace efficiency, and earnings. The role partners with product, engineering, and operations teams and requires Python, quantitative modeling, experimentation, and at least two years of relevant experience.
About the job
Responsibilities
- Collaborate with engineering and product teams to design, implement, and iterate on features and algorithmic improvements for driver incentives and pay mechanisms.
- Design, develop, and deploy optimization models, algorithms, and systems for budget allocation, multidimensional cost-curve development, and incentive targeting.
- Write production model code and collaborate with software engineers to implement algorithms in production.
- Perform exploratory data analysis to understand the marketplace and its users.
- Communicate findings and facilitate launch decisions with technical and non-technical stakeholders.
- Apply robust experimentation and causal inference methodologies to measure the impact of new features and strategies.
Requirements
- Advanced degree (MS or PhD, PhD preferred) in Operations Research, Applied Mathematics, Computer Science, Statistics, Engineering, or a related quantitative field, or equivalent work experience.
- 2+ years of hands-on experience in optimization, causal inference, or machine learning.
- End-to-end experience with data querying, aggregation, analysis, and visualization.
- Proficiency with Python.
- Strong collaboration and communication skills.
- Experience adopting new methods and techniques.
- Experience designing, running, and analyzing A/B tests.
Benefits
- Extended health and dental coverage, life insurance, and disability benefits.
- Mental health, family building, child care, and pet benefits.
- Lyft-funded Health Care Savings Account.
- RRSP plan with company match.
- Flexible paid time off for salaried team members; hourly team members receive 15 days paid time off, with an additional day per year of service.
- 18 weeks of paid parental leave top-up for biological, adoptive, and foster parents.
- Subsidized commuter benefits and Lyft ride credits.
- Hybrid work schedule with at least three office days per week, including Mondays, Wednesdays, and Thursdays.
- Flexibility to work from anywhere for up to four weeks per year.
- Expected base pay range: CAD $108,000–$135,000, excluding potential equity, bonus, and benefits.
Skills
Python, Optimization, Causal Inference, Machine Learning, Operations Research, Mathematical Programming, Control Theory, A/B Testing, Experimentation, Data Analysis, Data Visualization, Algorithm Design
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