Data Scientist, Decisions LUS

Lyft; Toronto; Hybrid; CAD 108,000 - 135,000; Full time

Job summary

A leading ride-sharing company in Toronto seeks a Data Scientist for the Lyft Urban Solutions team. The role focuses on using data to improve micromobility solutions, working collaboratively with various teams. Candidates should have a graduate degree in a quantitative field and experience with statistical models, SQL, and Python. The position offers a salary range of CAD $108,000 - $135,000 with various benefits, on a hybrid work schedule.

Benefits

Extended health and dental coverage

Mental health benefits

Family building benefits

Flexible paid time off

Subsidized commuter benefits

Qualifications

• 3+ years professional experience in a tech company.
• Ability to collaborate with team members.
• Passion for solving complex mathematical problems.

Responsibilities

• Partner with cross-functional teams to define problems.
• Develop and fit statistical or optimization models.
• Communicate findings and guide decisions.

Skills

Data analysis

Statistical modeling

Machine learning

SQL querying

Python programming

Education

M.S. or Ph.D. in Statistics, Operations Research, Mathematics, or related

Tools

Production model code

Data visualization tools

Job description

Data Scientist, Lyft Urban Solutions

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.

The Lyft Urban Solution team is developing the future of micromobility and is looking for a Data Scientist to inform and drive decision-making to help chart the way. From New York’s Citi Bike to San Francisco’s Bay Wheels, our micromobility systems depend on smart data-informed decisions to operate efficiently and at scale. Analyses, insights, and algorithms guide both planning and operations, and we’re looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems in micromobility

The set of problems tackled by the Lyft Urban Solutions Operations Technology Team is incredibly diverse. They cut across optimization, prediction, simulation, inference, transportation, analytics and mapping. We collaborate with and inform a wide range of stakeholders, from executives to hardware specialists to local market operations teams. We're looking for someone who is passionate about solving mathematical problems with data, and is excited about working in a fast-paced, innovative and collegial environment.

Responsibilities:

• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Develop and fit statistical, machine learning, or optimization models
• Write production model code; collaborate with Software Engineers to implement algorithms in production
• Design and implement both simulated and live experiments
• Analyze experimental and observational data; communicate findings; guidefacilitate launch decisions

Experience:

• M.S. or Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields or related work experience
• 3+ years professional experience in a technology company setting involving a product
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including SQL querying, aggregation, analysis, and visualization
• Proficiency with Python, ideally including both exploratory analyses/visualizations and building production models , or another interpreted programming language like R
• Ability to collaborate and communicate with others to solve a problem

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 - $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.