Senior Manager, Product Analytics

CLEAR - Corporate•New York, NY

55d•$200,000 - $230,000•Onsite

About The Position

Have you ever had that green-light feeling? When you hit every green light and the day just feels like magic. CLEAR's mission is to create frictionless experiences where every day has that feeling. With more than 30+ million passionate members and hundreds of partners around the world, CLEAR’s identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or right on your phone, CLEAR connects you to the things that make you, you - unlocking easier, more secure, and more seamless experiences - making them all feel like magic. As we scale, we’re investing deeply in data, experimentation, and analytics to improve how we make decisions and serve our members. We’re looking for a talented, hands-on Product Analytics Senior Manager to join us at a moment when foundational decisions matter most. This is not a “steady state” role. Instead, you’ll scale the product analytics function at CLEAR from an early stage: defining strategy, designing systems, shaping instrumentation, and moving us toward mature experimentation and user understanding. You’ll roll up your sleeves, influence cross-functional teams, and help instill a culture of measurement and data-driven decision-making across product, marketing, and engineering.

Requirements

7+ years experience in product analytics, data science, business analytics, or related fields with 2+ years leading teams.
Proven track record standing up or significantly scaling product analytics and experimentation capabilities in a tech or consumer product environment.
Fluency in SQL, experiment design (statistical rigor, power analysis, etc.), attribution, funnel & cohort analysis, and metric design. Experience with leading decisions around third party experimentation tooling.
Strong hands-on experience with product analytics tools (e.g. Heap, Amplitude, Mixpanel, etc.) and BI / dashboarding systems.
Solid understanding of data infrastructure, ETL pipelines, event logging, data governance, and how to ensure data integrity.
Exceptional communicator: you can translate complex analyses into clear, compelling narratives that drive decisions.
Strategic but pragmatic: you know when to ship “good enough” and when to perfect.
Bias for action, comfort with ambiguity, and willingness to get your hands dirty.
Leadership presence, collaborative spirit, and the ability to influence across functions.

Responsibilities

Drive adoption of CLEAR’s front-end measurement and tracking framework: taxonomy, event definitions, data governance, instrumentation standards.
Standardize the workflow around experimentation across our product surfaces.
Build reliable analytics pipelines in collaboration with Data Engineering, ensuring data quality, consistency, and scalability. Evangelize the perspective that data is a first-class product coming from our systems.
Define and socialize core metrics and KPIs across product lines and verticals. Drive a culture of accountability around performance.
Deliver dashboards and analyses that distill complexity into clarity for product teams, leadership, and business stakeholders.
Create frameworks for feature evaluation, long-term holdout analyses, funnel optimization, and user behavior deep dives.
Empower teams via self-service tooling and documented analytics processes to reduce requests for ad-hoc data and analysis support.
Build learning loops: lead post-mortems, root-cause analyses, and knowledge sharing across the org.
Build, lead, and grow a team of product analysts and data scientists.
Mentor and elevate analyst capabilities, instilling rigor around experiment design, causal reasoning, and communication of uncertainty.
Be a bridge across functions. Partner tightly with Product, Engineering, Design, Data, and Operations teams to align on goals and guardrails.
Advocate for analytics infrastructure and tooling investments — recommend platforms, augment the stack, and help scale our capabilities.
Evaluate new methodologies that factor in our complicated airport environment. Drive the evolution of A/B testing toward more complex test frameworks like multi-armed bandits, sequential tests, and causal inference, then establish best practices.
Stay current on industry trends and bring in novel ideas that move the needle.