Data Science, Decisions - Airports
Lyft is hiring a Data Science, Decisions - Airports in Toronto, Canada. It pays $108k a year and Level rates it ; you can apply on Lyft.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- The posting mentions data science, experiment design and sql among its tools and skills.
- Level classes it as a mid-level role.
- Lyft has 177 other open roles on Level.
AI in this role
Leverage data science and decision frameworks to optimize airport marketplace products and drive business growth at Lyft.
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. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features.
The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As a Data Scientist on the Airport team, you will collaborate with our team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth.
The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as:
- What rider segments are present at airports and how can we address their major pain points to grow our airport marketshare?
- What new airport product features can we introduce to grow rider demand?
- Are we able to forecast rider demand and use this prediction to adjust ride offerings or improve the rider experience?
- How can we optimize ride offerings for each rider to maximize conversion?
Responsibilities
- Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
- Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions
- Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes, identifying opportunities for growth and efficiency and recommending technical solutions to drive business impact
- Understand the complex business dynamics at Airports, specifically how Airport products differ from traditional rideshare marketplaces, to propose enhancements that compliment Lyft-wide products
- Present findings, recommendations, and results to senior leadership and cross-functional stakeholders
- Establish metrics that measure the health of our products, the business, as well as the rider and driver experience
Experience:
- Degree in a quantitative field (advanced degrees preferred) such as Statistics, Economics, Computer Science, Engineering, Applied Mathematics, or related discipline; or equivalent practical experience
- 4-6+ years of industry experience in a data science or analytics role
- End-to-end experience with data, including querying, aggregation, analysis, and visualization, to provide actionable insights and reusable frameworks
- Experience with experimentation, including user splits and time splits to accurately measure impact
- Ability to manage, influence, negotiate, and inspire others in a fast-moving environment
- Proficiency in SQL and Python - you can deep dive into large amounts of data, draw meaningful insights, dissect business issues and draw actionable conclusions
- Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration
- Exceptional communication skills with the ability to craft a compelling story and concisely present recommendations across teams and levels including both technical and non-technical audiences
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 $108,000 - CAD $135,000, 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.
How we rate this
Data Science, Decisions - Airports at Lyft rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
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- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where experiment design was part of your work. What did you do?
- Tell me about a project where sql was part of your work. What did you do?
- Tell me about a project where python was part of your work. What did you do?
- Tell me about a project where forecasting was part of your work. What did you do?
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- List these exact terms on your resume: Data Science, Experiment Design, SQL, Python, and Forecasting. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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