Sr. Product Marketing Manager - Measurement, Data & Audiences

Responsibilities:

Data Commercialization & Audience Go-to-Market

Audience Strategy: Own the end-to-end go-to-market strategy for Lyft’s first-party audience data, defining how real-world mobility signals and consumer journeys are packaged into high-value targeting segments.

Value Positioning: Develop compelling narratives, positioning frameworks, and sales enablement tools that clearly articulate the unique value of Lyft’s deterministic identity and location-based data.

Commercial Design: Partner with Product, Data Science, and Finance to define pricing frameworks and packaging structures for audience segments and advanced data targeting features.

Measurement, Attribution & Reporting Strategy

Attribution GTM: Drive the commercial rollout and adoption of in-house conversion modeling, multi-touch attribution, and offline-to-online conversion capabilities built by the Ad Infrastructure team.

Reporting & Interfaces: Inform the commercial requirements for advertiser-facing reporting systems, ensuring data transparency, ease of campaign management, and frictionless ROI reporting.

Market Education: Translate complex technical ad tech concepts (e.g., event data generation, signals, data clean rooms) into clear, compelling narratives for sales teams, brands, and top‑tier agencies.

Ecosystem & Bespoke Data Partnerships

Strategic Alliances: Identify, evaluate, and lead the development of bespoke data partnerships with high-value external platforms, brands, and ecosystems to create custom, mutually beneficial data‑sharing or co‑targeting opportunities.

Commercial Deal Structuring: Partner with leadership, Legal, and Finance to influence commercial negotiations, governance models, and revenue‑sharing structures for unique data collaboration agreements.

Partner Strategy & Accountability: Manage relationships with key third‑party measurement providers, verification partners, and data networks; drive joint business plans, QBRs, and partner prioritization frameworks optimized for audience scale and revenue impact.

Infrastructure Collaboration: Partner with Ad Infrastructure PMs, AdTech, and Engineering to ensure external partner connections, custom clean room setups, and attribution tools are optimally implemented and scalable.

Experience:

10+ years of experience in digital advertising, with meaningful depth in measurement, attribution, ad tech infrastructure, or data‑driven commerce/retail media.

Deep Technical & Data Literacy: Strong knowledge of the ad tech data ecosystem, including conversion modeling, third‑party measurement integrations (offline/online conversions, viewability), CDPs, and data clean rooms.

Strategic Partnership Experience: Demonstrated experience structuring, negotiating, and growing commercial partnerships with technology vendors, measurement providers, or bespoke data platforms.

GTM Expertise: Experience developing market positioning, packaging, and pricing frameworks for data products, SaaS measurement tools, or complex ad tech solutions.

Cross‑Functional Leadership: Exceptional collaboration skills; proven ability to bridge commercial and technical teams, working seamlessly across Sales, Product, Engineering, Data Science, Legal, and Finance.

Analytical Rigor: Strong financial modeling and analytical skills; ability to build data‑backed business cases, evaluate ecosystem dynamics, and model complex partner revenue scenarios.

Education: Bachelor’s degree or equivalent experience.

Preferred

Prior experience in a product marketing, business development, or strategic partnerships role directly supporting an Ad Infrastructure, Data, or Measurement product line.

Experience establishing and growing custom or bespoke data monetization programs at a commerce media network, retail media network (RMN), mobility platform, or high‑growth digital publisher.

Familiarity with privacy‑safe data collaboration methodologies, clean room architectures, and advanced attribution frameworks.

Experience building and managing joint business plans with major agency holding companies and strategic data brokers to drive incremental ad spend.

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 $143,000 - $178,750, 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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