---
title: 'Staff Applied Scientist at Lyft'
canonical: 'https://feeny.ai/job/staff-applied-scientist-lyft-san-francisco-qyccpzrkrx9c'
type: 'job'
last_seen: '2026-09-15'
---

# Staff Applied Scientist at Lyft

- **Company:** Lyft
- **Location:** San Francisco, CA
- **Posted:** 2026-07-26
- **Last confirmed live:** 2026-09-15
- **Apply:** https://app.careerpuck.com/job-board/lyft/job/8649343002?gh_jid=8649343002

## 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 an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts.

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 decision frameworks.

## Responsibilities

- Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
- Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries.
- Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.
- Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems
- Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes
- Drive collaboration and coordination with cross-functional teams

## Experience

- M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields
- 2+ years of algorithms experience in a technology company setting
- Proficiency with Python and working in a production coding environment
- Passion for solving unstructured and non-standard mathematical problems and building impactful machine learning models leveraging expertise in one or multiple fields.
- Strong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models
- Strong verbal and written communication skills with a good track record of collaborating with others to solve a problem

Benefits:

- Great medical, dental, and vision insurance options with additional programs available when enrolled
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- 401(k) plan with company match to help save for your future
- In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Subsidized commuter benefits
- 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 $193,600 - $242,000, 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.

## About Lyft

## Company Overview
- **One-liner**: Lyft operates a ride-hailing, bikeshare, and scooter platform that connects drivers and riders, aiming to reduce personal car ownership and make cities more livable.
- **Entity Type**: Public (NASDAQ: LYFT)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2012
- **Founders**: Logan Green and John Zimmer

## Core Business
- **Primary industry/industries**: Mobility, Transportation, Ride-hailing, Micromobility
- **Target customers**: B2C (riders and drivers), B2B (Lyft Business for enterprise commutes), and public sector (transit partnerships)
- **Mission or purpose statement**: "To serve and connect" — building a more connected world, ride by ride.

## Products & Services
- **[Lyft Rideshare]**: The core on-demand ride-hailing service connecting passengers with drivers. Type: Platform / Service.
- **[Lyft Pink]**: A subscription membership offering perks like discounted rides, priority airport pickups, and free bike/scooter unlocks. Type: Subscription.
- **[Lyft Business]**: A suite of tools for companies to manage employee commutes, client rides, and delivery logistics. Type: B2B SaaS / Service.
- **[Lyft Bikes & Scooters]**: Shared electric bikes and scooters available in select cities, including the Bixi network in Montreal. Type: Micromobility Service.
- **[Lyft Flexdrive]**: A car rental program for drivers who don't own a vehicle, enabling them to earn on the platform. Type: Service / Fleet Management.
- **[Lyft Ads]**: In-app advertising platform allowing brands to reach riders and drivers. Type: Ad Tech / Marketplace.

## Market Standing
- **Valuation/Market Cap**: Approximately $4.5 billion (as of mid-2025, market cap fluctuates). **Not publicly available** for private valuation — public company.
- **Key Metric**: Annual Revenue of approximately $4.4 billion (FY 2023), with $1.3 billion in Q1 2025 reported revenue.
- **Notable Investors/Partners**: Major institutional investors include Fidelity, Vanguard, and BlackRock. Key partners include Uber (in some markets, e.g., transit data sharing), Motivate (bikeshare operator), and various municipal transit agencies.
- **Growth Signals**: Launched Lyft Ads in 2024; expanded into autonomous vehicle partnerships (Waymo, Motional); opened new offices in Toronto (2024) and Mexico City (2022); strong recovery in ride volumes post-pandemic.

## Competitive Advantages
- **Differentiated brand and culture**: Known for a friendlier, more community-oriented brand compared to competitors, with a focus on driver and rider safety.
- **Integrated multimodal platform**: Combines ride-hailing, bikes, scooters, and public transit info in one app, making it a one-stop mobility solution.
- **Strong transit partnerships**: Deep integrations with city transit agencies (e.g., Montreal's Bixi, LA Metro) provide a unique public-sector moat.
- **Data & network effects**: Large dataset on urban mobility patterns enables better routing, pricing, and demand prediction.

## Strategic Focus
- **Autonomous vehicle (AV) readiness**: Building partnerships and infrastructure to integrate AVs into the platform, positioning for a future without human drivers.
- **Advertising revenue**: Scaling Lyft Ads to create a new high-margin revenue stream, leveraging its large user base.
- **International expansion**: Selectively entering new markets (e.g., Canada, Mexico) and deepening presence in existing ones via bikeshare and transit.
- **Profitability**: Continued focus on operational efficiency and cost discipline to achieve sustained GAAP profitability.

## Why Work Here
- **Culture**: Lyft emphasizes a welcoming, inclusive culture with core values like "Be yourself," "Make it happen," and "Uplift others." The company fosters a strong sense of belonging through Employee Resource Groups (ERGs) and community events.
- **Remote/Hybrid/Office Policy**: Hybrid model — employees are expected in the office a few days a week, with flexibility. Offices are designed with tech-equipped workspaces, stocked kitchens, and themed rooms.
- **Notable Perks**:
    - **Health & Well-being**: Comprehensive medical, dental, vision; free One Medical membership; free access to therapists via Modern Health.
    - **Time Off**: Unlimited paid vacation for salaried US employees; generous PTO for hourly employees.
    - **Parental Leave**: 18 weeks of paid leave for all new parents (biological, adoptive, foster).
    - **Financial**: 401(k) plan with financial training sessions.
    - **Commute**: Free Lyft Pink membership; pre-tax commuter benefits.
    - **Learning**: Udemy subscription for professional development; mentorship programs for interns and new grads.
    - **Office Environment**: Dog-friendly offices; regular team offsites and social events.
- **Engineering Culture**: Known for high-impact work on large-scale distributed systems, machine learning, and mobile engineering. Early-career talent is highly valued, with structured mentorship and real project ownership.

## Sources
1. [Lyft Careers](https://www.lyft.com/careers)
2. [Lyft Life at Lyft](https://www.lyft.com/careers/life-at-lyft)
3. [Lyft Early Talent Programs](https://www.lyft.com/careers/early-talent)
4. [Lyft Homepage](https://www.lyft.com/)
5. [LinkedIn Lyft](https://www.linkedin.com/company/lyft)

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