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Assistant Front Store Manager, Hourly Part Time Day
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Assistant Front Store Manager, Hourly Part Time Day
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Markham, ON
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To assist the Front Store Manager (FSM) in managing the human, physical and financial resources of the store and in ensuring that store objectives are achieved by focusing on improving…
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Added 54 mins ago
Janitorial & Food Beverage Supervisor
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Drone.vet

Data Scientist, Decisions - Mapping

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 31, 2026
Experience: 1+ years experience in a data science role or analytics role
Posting language: English
Posted: Oct 1, 2026

Apply About employer

Applications open in a new tab.

Original job 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.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science Is At The Heart Of Lyft’s Products And Decision-making. You Will Leverage Data And Rigorous, Analytical Thinking To Shape Our Mapping Products And Make Business Decisions That Put Our Customers First. This Will Involve Identifying And Scoping Opportunities, Shaping Priorities, Recommending Technical Solutions, Designing Experiments, And Measuring The Impact Of New Features. You Will Help Us Solve Some Of The Most Impactful Problems In Mapping, Including

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?

Responsibilities

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
Design and analyze online experiments; communicate results and act on launch decisions
Develop analytical frameworks to monitor business and product performance
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

Experiences

Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
1+ years experience in a data science role or analytics role
Proficiency in SQL - able to write structured and efficient queries on large data sets
End-to-end experience with data, including querying, aggregation, analysis, and visualization
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 oral and written communication skills, and ability to collaborate with and influence cross-functional partners
Experience in applying machine learning techniques a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
Experience working with ETL pipelines a 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 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

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 $88,000 - CAD $110,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Apply About employer

More about this job

Responsibilities

Use data and analytical frameworks to identify opportunities, improve mapping products, and guide product and business decisions. Design and analyze experiments, establish performance and customer-experience metrics, and communicate findings to cross-functional partners.

Requirements

A quantitative degree or relevant work experience and at least one year in data science or analytics are required, along with strong SQL and end-to-end data analysis experience. Candidates should have programming experience in Python or R, familiarity with data science and machine learning libraries, and experience with experimentation, statistical analysis, and communicating recommendations to stakeholders.

Skills

Data Science
SQL
Python
R
Data Analysis
Data Visualization
Machine Learning
PyTorch
TensorFlow
Keras
Online Experimentation
Statistical Analysis
ETL Pipelines
Spatial Data
Product Analytics
Cross-Functional Collaboration

Benefits

Extended Health Coverage
Dental Coverage
Life Insurance
Disability Benefits
Mental Health Benefits
Family Building Benefits
Child Care Benefits
Pet Benefits
Health Care Savings Account
RRSP With Company Match
Paid Time Off
Paid Parental Leave
Commuter Benefits
Lyft Ride Credits

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Mapping
Spatial Data
Route Recommendations
Travel Time Estimation
SQL
Python
R
PyTorch
TensorFlow
Keras
Machine Learning
Reinforcement Learning
Online Experiments
Statistical Analysis
Data Querying
Data Aggregation
Data Visualization
ETL Pipelines
Analytical Frameworks
Product Performance Metrics
Rider Experience
Driver Experience
Product Strategy
Business Strategy
Personalization
Segmentation
A/B Testing
Cross-Functional Collaboration
Navigation

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