{"id":1601878,"url":"https://alion.io/job/lyft-senior-data-scientist-causal-inference-2","title":"Senior Data Scientist, Causal Inference","company":{"id":234,"name":"Lyft","domain":"lyft.com","url":"https://alion.io/company/lyft","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":88,"open_postings":22,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":48,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","New York, United States","Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":148000,"max":185000,"currency":"USD","period":"year","gross":null,"usd_annual":185000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-06-10T22:16:01Z","employer_posted_date":"2026-09-04","last_verified_at":"2026-10-12T12:27:05Z","board_verified":true,"closed_at":null,"days_open":123,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":123},"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.\n 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.\nAs 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.\nResponsibilities:\nDeliver 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.\nOwn complex domains and develop long-term roadmaps to maximize business impact.\nBuild statistical pipelines, write production code, and design/analyze experiments.\nParticipate in the science on-call rotation to ensure automated campaigns operate successfully.\nExperience:\nAdvanced degree in statistics, economics, mathematics, or equivalent industry experience.\n4+ years of industry experience in causal inference or data science.\nProven ability to apply statistics to unstructured problems and deliver measurable results.\nDeep technical expertise in causal inference and tackling challenging measurement problems.\nExpertise in marketing mix modeling is highly preferred.\nExpertise in SQL and experience with large-scale data platforms.\nProficiency in Python and working within production coding environments.\nBenefits: \nGreat medical, dental, and vision insurance options with additional programs available when enrolled\nMental health benefits\nFamily building benefits\nChild care and pet benefits\n401(k) plan with company match to help save for your future\nIn addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off\n18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible\nSubsidized commuter benefits\nMonthly Lyft credits and complimentary Lyft Pink membership\nLyft 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.\nLyft 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\nThe expected base pay range for this position in the San Francisco area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. 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