Jobs
Benefits & Perks
•Healthcare
•Mental Health
•401(k)
•Parental Leave
•Commuter Benefits
•Pet Insurance
•Healthcare
•Mental Health
•401k
•Parental Leave
•Commuter
•Pet Insurance
Required Skills
Python
Machine Learning
Operations Research
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 Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Rider Engagement is a fast-growing team within Pricing, focused on developing rider-facing engagement levers and optimizing user pricing experience to drive both short term and long term business outcomes.
As an Applied Scientist specializing in Machine Learning and Operational Research on this team, you will develop mathematical models and launch algorithms that power core discounting systems and pricing decisions. You will be hands-on with building ML and optimization models, productionizing pipelines, building and scaling systems that deal with real-time data processing, large data storage and critical business problems that have a big impact on the marketplace and customer experience. You will get exposure to diverse problems across optimization, prediction, machine learning, and inference; you will collaborate with teammates and stakeholders to build and scale our systems and enhance algorithms.
We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decisioning frameworks.
Responsibilities:
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Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
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Write production quality code. Design, build and deploy production-grade ML models.
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Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems.
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Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems
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Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes
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Drive collaboration and coordination with cross-functional teams
Experience:
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M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields
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2+ years of machine learning experience in a technology company setting
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Proficiency with Python and working in a production coding environment
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Passion for solving unstructured and non-standard mathematical problems, and building impactful machine learning models leveraging expertise in one or multiple fields.
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Strong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models
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Strong verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem
Benefits:
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Great medical, dental, and vision insurance options with additional programs available when enrolled
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Mental health benefits
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Family building benefits
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Child care and pet benefits
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401(k) plan with company match to help save for your future
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In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
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18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
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Subsidized commuter benefits
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Monthly Lyft credits and complimentary Lyft Pink membership
Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
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 3 days per week 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 San Francisco area is $140,800 - $176,000, 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.
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About Lyft

Lyft
PublicLyft, Inc. is an American company offering ride-hailing services, motorized scooters, and bicycle-sharing systems in the United States and Canada, and, via its Free Now mobile app, Europe. Lyft is the second-largest ridesharing company in the United States after Uber.
1,001-5,000
Employees
San Francisco
Headquarters
$3.2B
Valuation
Reviews
2.7
10 reviews
Work Life Balance
3.8
Compensation
2.1
Culture
2.3
Career
2.0
Management
1.8
25%
Recommend to a Friend
Pros
Flexible scheduling and work-from-home options
Easy money and side hustle opportunities
Meet new people with good conversations
Cons
Unfair pay structure and low compensation
Easy deactivation based on rider complaints
Poor customer support for drivers
Salary Ranges
29 data points
Mid/L4
Senior/L5
Mid/L4 · Data Engineer
2 reports
$191,262
total / year
Base
$147,125
Stock
-
Bonus
-
$169,325
$213,200
Interview Experience
5 interviews
Difficulty
4.0
/ 5
Duration
14-28 weeks
Offer Rate
100%
Experience
Positive 60%
Neutral 40%
Negative 0%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview/Take-home Challenge
5
System Design Interview
6
Onsite/Virtual Interviews
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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