Home › Companies › Lyft › Data Analyst, Operations Planning
Data Analyst, Operations Planning
Lyft · New York, NY · Hybrid · Active · $82,800–$103,500 / year · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | Lyft |
| Title | Data Analyst, Operations Planning |
| Normalized title | - |
| Department / team | LUS Central Operations |
| Location | New York, NY, United States |
| Work model | Hybrid / Hybrid |
| Employment type | - |
| Salary | $82,800–$103,500 / year |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | 2026-05-28 / 2026-06-06 |
| Changed / last seen | 2026-06-06 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Lyft. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in LUS Central Operations. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Lyft |
| Source | 5fc2601d-43e7-4c04-81d6-28aa2a8c9d05 |
| ATS provider | Greenhouse |
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.
Data and analytics are at the heart of Lyft's products and decision-making. As a member of the Lyft Urban Solutions team, you will play a key role in shaping the future of bike & scooter share by leveraging data to improve the performance of our bikeshare and scooter markets across America. A successful candidate thrives in a dynamic and collaborative environment, has a natural curiosity, and isn’t afraid to dive deep.
In this role, you will collaborate closely with Operations, Hardware, Software, Product and Finance teams to identify opportunities and gaps in performance. You will work in a fast-paced environment where your analytical insights will directly impact strategic decisions around hardware product development, staffing, and product changes, ultimately driving better performance and long-term investments in micromobility infrastructure.
We’re looking for a passionate and driven Data Analyst to tackle some of the most complex and impactful challenges in micromobility. If you’re excited about shaping the future of urban mobility through data, we’d love to hear from you.
Responsibilities:
Partner with Product, Engineering, Data Science & Analytics, Operations, Finance and other cross-functional stakeholders on initiatives to improve operational performance
Develop frameworks and scalable processes to streamline reporting, drive decision-making and prioritization
Forecast operational requirements needed to maintain high service levels and meet contractual and financial targets
Work with our bike & scooter share markets to deliver ongoing support and deep dive analyses on performance; monitor and diagnose performance and present findings to key stakeholders
Collaborate with cross-functional teammates to tackle complex problems including: asset maintenance, system health and labor forecasting
Experience:
3+ years experience in data analytics in a high-growth environment, preferably a consulting, operations or transportation / logistics space
Bachelor's Degree or equivalent relevant professional experience
Highly skilled in SQL and quantitative analysis. You can deep dive into large amounts of data, draw meaningful insights, dissect business issues and draw actionable conclusions
Ability to develop scalable approaches and produce data visualizations to drive business insights and provide tangible solutions; experience building dashboards for performance analysis is a plus
Extreme comfort working with ambiguity. Ability to translate unclear issues or unstructured problems into clearly defined requirements with minimal oversight
Strong interpersonal skills, with the ability to build relationships, trust and influence with cross-functional partners
Great communication (listening, written, and oral) skills with the ability to present findings & recommendations targeted to the audience in question
Strong attention to detail, structured thinking and experiences developing processes to reduce human error
Adept at contextualizing real world operations into analytical problem solving
Passionate about sustainable mobility and active transportation
A strong sense of product ownership - you’re constantly looking for ways to improve the customer’s experience and aren’t afraid to get your hands dirty to do so
Bonus: Proficiency in Python and associated data science libraries
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 New York City area is $82,800 - $103,500, 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.
Full job record
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| Source ID | 5fc2601d-43e7-4c04-81d6-28aa2a8c9d05 |
| Board ID | 5fc2601d-43e7-4c04-81d6-28aa2a8c9d05 |
| Provider | greenhouse |
| Provider Job Key | 8568512002 |
| Title | Data Analyst, Operations Planning |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York, NY |
| Department | LUS Central Operations |
| Team | — |
| Employment Type | — |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | base pay range for this position in the New York City area is $82,800 - $103,500, not inclusive of potential equity offering, bonus or benefits |
| Salary Min | 82,800 |
| Salary Max | 103,500 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://app.careerpuck.com/job-board/lyft/job/8568512002?gh_jid=8568512002 |
| Apply URL | https://app.careerpuck.com/job-board/lyft/job/8568512002?gh_jid=8568512002 |
| First Seen At | 2026-06-06 07:33:26Z |
| Last Seen At | 2026-06-06 20:29:23Z |
| Last Checked At | 2026-06-06 20:29:23Z |
| Last Changed At | 2026-06-06 07:33:26Z |
| Inactive At | — |
| Source Posted At | 2026-05-28 18:18:09Z |
| Source Updated At | 2026-06-05 04:29:24Z |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=lyft/date=2026-06-06/2026-06-06T20-29-23-450Z-504c4a22ad24d76f0237316a7e4ab4918cafef3b5579b1ea51792a133c50aa43.json |
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