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Technology

Senior Data Scientist, Causal Inference

LyftSeattle, WA, United StatesFull-time$136,160 - $170,240Posted Oct 25, 2026

Lyft is hiring for the position of Senior Data Scientist, Causal Inference in Seattle, WA, United States. The listing describes it as a full-time, senior position with hybrid working.

Written by Dev Global Jobs

DGJ summary of this job

Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.

Lyft is hiring for the position of Senior Data Scientist, Causal Inference in Seattle, WA, United States. The listing describes it as a full-time, senior position with hybrid working.

From the advert, the main requirements are 4+ years of experience.

The advert mentions Python, SQL and statistics among the skills and tools for this role.

Pay stated in the listing: $136,160 - $170,240.

Benefits mentioned in the advert: health insurance, pension or retirement plan, paid time off, parental leave and bonus.

Visa sponsorship is not mentioned. Applicants from outside United States should check the official work permit route before applying.

Dev Global Jobs found this job on Greenhouse on Oct 25, 2026; the apply link was last checked on Oct 28, 2026.

Employer
Lyft
Location
Seattle, WA, United States
Work mode
hybrid
Job type
Full-time
Level (from the title)
senior
Pay
$136,160 - $170,240
Experience asked
4+ years
Found
Oct 25, 2026 on Greenhouse
Employer text
535 words, about 2 min to read
Skills named in the advert
PythonSQLstatistics
Before you apply
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  • Compare your own experience with the 4+ years the advert asks for, and show it clearly near the top of your CV.
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Only on Dev Global Jobs

DGJ Insight

Our own data about this role and place, from official statistics and our live job index.

Updated Nov 1, 2026
Pay benchmark
Average wage, United States
$86,977 average / year

This job's listed pay is 76% above the benchmark.

This job: $136,160 to 170,240

Source: OECD Average annual wages, 2025

Work permit route
  • H-1B specialty occupation: Employer petition, bachelor's degree or higher in the specialty; annual cap and lottery
  • L-1 intracompany transferee: Employees of a related company abroad transferring to a US office
  • O-1 extraordinary ability: Evidence of extraordinary ability in sciences, arts, education, business or athletics

Official routes: USCIS

Freshness
Apply link answered

Answered at our last check on Oct 28, 2026.

Job description

About the role

Full text from the employer, as published on Greenhouse, arranged into sections. Nothing added or removed.

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products.

As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels.

01Responsibilities

  • Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems.
  • Own complex domains and develop long-term roadmaps to maximize business impact.
  • Build statistical pipelines, write production code, and design/analyze experiments.
  • Participate in the science on-call rotation to ensure automated campaigns operate successfully.

02Experience

  • Advanced degree in statistics, economics, mathematics, or equivalent industry experience.
  • 4+ years of industry experience in causal inference or data science.
  • Proven ability to apply statistics to unstructured problems and deliver measurable results.
  • Deep technical expertise in causal inference and tackling challenging measurement problems.
  • Expertise in marketing mix modeling is highly preferred.
  • Expertise in SQL and experience with large-scale data platforms.
  • Proficiency in Python and working within production coding environments.

03Benefits

  • 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 Seattle area is $136,160 - $170,240, 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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