# Staff Data Scientist, Decisions - Partnership, Loyalty & Pay

**Company:** [Lyft](https://hotfix.jobs/companies/lyft)
**Location:** New York, NY
**Role:** Data Science
**Salary:** $176k – $220k/yr
**Experience:** 6+ years
**Skills:** Causal Inference, Machine Learning, Experimental Design, Python, SQL, A/B Testing, Difference-In-Differences, Synthetic Control
**Posted:** 2026-06-01

> As a Staff Data Scientist, Decisions on the Partnership, Loyalty & Pay team, you will leverage data, analytical thinking, and causal inference to shape product vision and make business decisions. You will drive the data science roadmap, partner with cross-functional teams, and apply advanced analytics and experimentation techniques.

## Job Description

## Responsibilities:

* Drive the data science roadmap across the Partnership, Loyalty, and Pay teams. Be a primary participant in defining team goals and setting the priorities of projects for the team to address
* Partner with org leads in product, engineering, UX research, design, marketing, and business development to initiate, design, develop, and scale zero-to-one programs and drive business strategy through data-centric recommendations
* Define and maintain key objectives and metrics to align with the overarching goals of Rider, Marketplace, and Lyft - including incrementality measurement for partnerships, retention impact of loyalty programs, and health of Pay products
* Apply modeling, advanced analytics, experimentation, and causal inference techniques (e.g., A/B testing, difference-in-differences, synthetic control, quasi-experimental methods) to drive decision-making at Lyft
* Drive cross-org impact and alignment, shaping product and business strategy through data-centric presentations to VP and C-level stakeholders
* Advise teams on best practices. Be a thought leader and go-to expert on measurement, incrementality, and causal inference for PLP stakeholders and dependency teams
* Provide technical guidance and mentorship to junior and mid-level team members on solution design and implementation; lead code reviews and elevate team-wide technical standards

## Experience:

* Degree in a quantitative field (e.g., Stats, Econ, Math, CS) at the Master's or PhD level, or equivalent professional expertise in high-impact environments
* 6+ years of professional experience in data science, with a history of implementing causal models that result in tangible business value
* Subject matter expertise in the realms of causal inference, machine learning, and experimental design
* Sharp product sense and practical experience utilizing various causal methodologies
* Technical mastery of Python and SQL for data analysis and modeling
* Experience crafting sophisticated measurement frameworks, including counterfactual analysis and advanced experimentation to determine true incrementality
* Capability to unite cross-org partners, influence technical systems, and challenge existing scientific premises to steer product vision
* Strong communication skills to explain complex scientific results and the balance between velocity and rigor to executives and peers
* Proven track record of managing ambiguous problem spaces and converting broad business needs into structured scientific roadmaps
* Dedication to mentoring fellow scientists, raising the bar for technical excellence, and setting standards for modeling and reasoning

## 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

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