Data Science, Decisions - Rider AV at Lyft, Inc.

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

21 Dec, 25

Salary

135000.0

Posted On

22 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Causal Inference, Optimization, Algorithm Development, Exploratory Data Analysis, Experimental Design, Collaboration, Communication, Real-Time Systems, Data Processing, SQL, Spark, Dynamic Pricing, Supply Chain Optimization

Industry

Ground Passenger Transportation

Description

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 work in dynamic environments, where we embrace moving quickly to build the world’s best transportation. We take on a variety of problems ranging from shaping long-term business strategy with data, making short-term critical decisions, and building algorithms/models that power our internal and external products. As a Data Scientist you'll partner closely with product, engineering, and operations leaders to build and scale our real-time incentive systems, shape long-term strategy, and deliver on critical business goals that directly impact Lyft's marketplace efficiency and driver engagement. The ideal candidate will have strong experience in algorithm development (particularly in optimization, machine learning, or causal inference), thrive in a fast-paced environment, and possess a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for real-time incentives. Design, develop and deploy machine learning models, algorithms, and systems to optimize real-time supply management, including Bonus Zone budget allocation and Priority Mode effectiveness. Perform exploratory data analysis to gain a deeper understanding of problems Communicate findings and facilitate launch decisions Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies. Experience: Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience. 2+ years of hands-on technical experience in machine learning, causal inference, optimization, or data science, preferably with applications in real-time systems or marketplace dynamics. Proven track record of leveraging data science, optimization, and/or machine learning to drive significant business outcomes. Strong understanding of experimental design and causal inference. Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences. Hands-on experience with large-scale data processing (e.g., Spark, SQL) and machine learning frameworks is highly desirable. Familiarity with real-time bidding, dynamic pricing, or supply chain optimization is a strong 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 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 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. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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Responsibilities

Collaborate with engineering and product teams to design and implement algorithmic improvements for real-time incentives. Ensure robust experimentation methodologies are applied to measure the impact of new features and strategies.