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Data Scientist, Decisions - Mapping

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

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
  • Drive cross-org 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
  • 4+ years experience in a data science role or analytics role
  • Proficiency in SQL - able to write structured and efficient queries on large data sets
  • 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 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 proudly pursues and hires a diverse workforce. 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 now if you wish to make such a request.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. 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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What You Should Know About Data Scientist, Decisions - Mapping, Lyft

At Lyft, we believe in connecting communities and providing safe, efficient rideshare experiences. We are currently on the lookout for a driven Data Scientist to join our Mapping team in Toronto, Canada. In this role, you will collaborate with a world-class team of engineers, product managers, and designers to enhance the quality of our mapping products. Your analytical expertise will directly impact our recommended routes and travel time estimations, ensuring they are as accurate as possible for our drivers. Imagine diving deep into our spatial data to identify opportunities for growth and efficiency in routing—this is where you will shine! As a Data Scientist at Lyft, you'll leverage data to shape our business decisions, identify key metrics for performance, and validate critical features affecting our routing algorithms. You will be at the core of problem-solving, addressing questions like how to enhance our map data quality and how to measure the success of our services. Your role will involve designing experiments and communicating results effectively to influence cross-functional partners. We're looking for someone with a quantitative background, solid experience in data science, and proficiency in SQL, Python or R, with a knack for applying machine learning techniques. If you're passionate about data and ready to implement your insights into actionable solutions in a fast-paced environment, we want to meet you at Lyft!

Frequently Asked Questions (FAQs) for Data Scientist, Decisions - Mapping Role at Lyft
What qualifications are needed to be a Data Scientist at Lyft?

To become a Data Scientist at Lyft, especially within the Mapping team, candidates typically need a degree in a quantitative field such as statistics, economics, or engineering, and ideally possess an advanced degree. Moreover, having at least 4 years of experience in a data science or analytics role, proficiency in SQL, and skills in programming languages like Python or R are essential. Familiarity with machine learning techniques is also a great advantage.

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What will I be doing as a Data Scientist at Lyft in Toronto?

As a Data Scientist on the Mapping team at Lyft, your primary responsibilities will revolve around leveraging data to enhance our mapping products. This includes analyzing spatial data to improve routing accuracy, designing online experiments to measure product performance, and collaborating with various teams to translate analytical insights into actionable strategies that prioritize customer satisfaction.

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How does Lyft support the work-life balance of its Data Scientists?

Lyft values the well-being of its employees by offering flexible paid time off for salaried team members, in addition to standard provincial holidays. You’ll enjoy a hybrid working schedule that allows flexibility to work remotely for a portion of the year, as well as benefits that support family and mental health, ensuring a balanced and supportive work environment for Data Scientists.

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What kind of projects will a Data Scientist on the Mapping team work on?

As a Data Scientist at Lyft, especially focusing on Mapping, you will work on pivotal projects that aim to enhance user experiences by improving map data quality and developing metrics to measure performance. You will tackle questions around travel estimation accuracy, assess the effectiveness of routing algorithms, and formulate technical solutions that drive business goals.

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What programming skills are essential for a Data Scientist at Lyft?

A successful Data Scientist at Lyft should be proficient in SQL for data management and querying large datasets efficiently. Skills in programming languages such as Python or R, especially with data science and visualization libraries, are crucial. Familiarity with machine learning libraries like PyTorch, TensorFlow, or Keras will also be beneficial, particularly for solving complex customer-oriented challenges.

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Common Interview Questions for Data Scientist, Decisions - Mapping
Can you describe your experience with data analysis and visualization?

In answering this question, showcase specific projects where you successfully analyzed data and presented it visually. Discuss the tools you used (like Python’s Matplotlib or R’s ggplot) and how your analyses led to actionable insights that benefitted your previous employer.

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How do you prioritize projects when multiple tasks are on the table?

When faced with multiple tasks, it’s essential to evaluate their business impact and urgency. Discuss your approach to stakeholder communication, maintaining transparency about timelines, and your method for aligning your efforts with team goals to ensure consistency and focus.

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What techniques do you use for online experimentation?

When tackling online experimentation, emphasize your understanding of A/B testing and how you design experiments to ensure statistical validity. Share past experiences where you tested hypotheses, analyzed results, and iterated on product features based on data-driven insights.

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Tell me about a time you had to explain a complex data concept to a non-technical audience.

It’s crucial to have both technical and interpersonal skills. Take this opportunity to describe a situation where you simplified complex data insights into layman’s terms. Illustrate your storytelling skills and emphasize how your communication facilitated understanding and decision-making among stakeholders.

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How do you ensure the data you are using is accurate and reliable?

Discuss your methodology for data validation, which might include cross-referencing sources, cleaning datasets, and utilizing ETL (Extract, Transform, Load) practices. Talk about the importance of maintaining an up-to-date data environment and how that affects your analysis.

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What is your experience with machine learning and its applications in data science?

Be prepared to dive into specific machine learning techniques you have applied in previous roles. Discuss algorithms you've implemented at scale, and share how they provided insights or solutions that directly affected your organization’s objectives or customer engagement strategies.

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How do you approach defining success metrics for projects?

Emphasize a thoughtful approach to stakeholder requirements, understanding business objectives, and defining KPIs that align with those goals. Explain past examples where well-defined metrics led to clearer project outcomes and facilitated successful evaluations post-implementation.

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Describe a time when you identified a significant opportunity or problem in your analysis.

Employ a scenario from a previous role where your analytical skills led to discovering a key issue or opportunity. Describe how you approached it, the analysis you conducted, and how your findings altered the course of action for your team or organization.

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What data science tools and technologies are you most comfortable using?

Share your familiarity with various data tools and languages, such as SQL, Python, or R, and the libraries you utilize for data manipulation and visualization. Mention any platforms you’ve used for data analytics or machine learning, showcasing a comprehensive skill set.

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Where do you see the future of data science in the rideshare industry?

Discuss innovation in data science, including machine learning advancements and how predictive analytics are shaping the rideshare experience. Describe how data will play a role in enhancing user experiences and operational efficiencies, and express your excitement about being part of that evolution at Lyft.

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Lyft is one of the leading ride-sharing companies in America offering services in ride-hailing, vehicles for hire, motorized scooters, a bicycle-sharing system, rental cars, and food delivery in the United States and select cities in Canada.

106 jobs
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BADGES
Badge ChangemakerBadge Diversity ChampionBadge Flexible CultureBadge Work&Life Balance
CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Customer-Centric
Social Impact Driven
Rapid Growth
BENEFITS & PERKS
Maternity Leave
Paternity Leave
Flex-Friendly
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
401K Matching
FUNDING
DEPARTMENTS
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TEAM SIZE
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
March 22, 2025

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