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About the Role

Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings.

Responsibilities

Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms.
Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting.
Write production model code; collaborate with Software Engineers to implement algorithms in production.
Perform exploratory data analysis to gain a deeper understanding of the marketplace and its users.
Communicate findings and facilitate launch decisions with technical and non-technical stakeholders.
Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies.

Requirements

Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Applied Math, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience.
2+ years of hands-on experience in optimization (preferred), causal inference, or machine learning.
End-to-end experience with data, including querying, aggregation, analysis, and visualization.
Proficiency with Python.
Strong ability to collaborate and communicate with others in a team setting.
Experience seeking out and adopting new methods and techniques.
Experience designing, running, and analyzing A/B tests to validate hypotheses and inform decision-making.

Skills

Optimization
Causal Inference
Machine Learning
Python
Data Analysis
A/B Testing

Location

Toronto

Work Type

Hybrid
In-office

Experience Level

2+ years

Education Level

MS or PhD

Salary/Compensations

CAD $108,000 - CAD $135,000

Benefits

Extended health and dental coverage options
Life insurance
Disability benefits
Mental health benefits
Family building benefits
Child care benefits
Pet benefits
Lyft funded Health Care Savings Account
RRSP plan with company match
Flexible paid time off policy
18 weeks of paid time off for new parents
Subsidized commuter benefits
Lyft ride credits

About the Company

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.
Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products.

Equal Opportunity

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.