Sr. Manager, Marketing Analytics

Build, manage, and develop a team of brand/pod analysts — owning hiring, onboarding, coaching, prioritization, and career growth.

Set the analytical and communication bar for the team and establish the operating rhythm from the ground up.

Create a collaborative, high-performing environment where a small team punches above its weight across a large brand surface.

Be accountable for trend monitoring, first-response investigations, and the full-funnel story (acquisition → engagement → retention → revenue) across the E&E brand portfolio.

Proactively surface opportunities and risks across brands and markets as well as influence strategy through data-driven recommendations.

As a player-coach — especially while the team is small — personally lead the most complex cross-brand investigations and executive readouts.

Own the consumption-and-translation layer for E&E: turn PRISM incrementality, MMM, and HALO model outputs into clear test, optimization, and expansion recommendations.

Partner with Data Science on test design priorities and surface measurement needs on behalf of the brands.

Enforce analytical rigor and consistency across brand stakeholders without ceding ground.

Own the E&E sections of leadership forums (QMO, WBR) and ad hoc leadership analysis, ensuring a consistent, unified read across ~17 brands.

Frame insights in terms of business impact, trade-offs, and recommended actions — the clear "what changed, why, so what, and now what."

Influence decision-making through strong storytelling and structured communication.

Serve as the senior analytics partner to E&E brand and PMG leads, owning the weekly and monthly cadence and setting clear expectations on what the team delivers.

Act as a key interface between Marketing Analytics and partner teams — Marketing, Product, Finance, PRISM, and BI/Ops — ensuring alignment on performance drivers.

Establish standardized frameworks, playbooks, and metric definitions so coverage of 46 brand/market combinations does not depend on heroics.

Champion the use of AI across the team — accelerating analysis, drafting narratives, and building repeatable workflows — and coach the team to adopt it.

Partner with BI/Ops and Measurement to automate manual load, and keep the E&E and Tinder operating models symmetric.

Bachelor's, Master's, or equivalent experience in a quantitative field (e.g., Economics, Statistics, Mathematics, Data Science, Business Analytics, or a related discipline).

Significant experience in analytics, business intelligence, or data analysis, including experience leading, coaching, or mentoring analysts. (Manager: prior or emerging people-management experience; Director: a track record of managing analysts, and ideally managers, through ambiguity.)

Experience owning senior stakeholder relationships and delivering in a fast-paced, high-ambiguity environment — ideally standing up or scaling a new function.

Proven ability to build, coach, and retain a high-performing analytics team, and to set standards for quality, communication, and impact.

Genuine appetite for management — you want to multiply a team's output, not just carry the title.

Comfort operating as a player-coach: leading the team while remaining hands-on on the hardest problems.

Strong SQL for querying and analyzing large datasets.

Proficiency with data visualization and BI tools (e.g., Tableau, Mode, Hex, Databricks).

Strong understanding of funnel analysis, cohort analysis, and behavioral analytics, and the ability to "connect the dots" across metrics into a narrative.

Working knowledge of experimentation and incrementality concepts — enough to partner credibly with Data Science and PRISM and to enforce rigor. You do not need to be a “modeler” but you need to be able to understand and speak to them.

Actively uses AI tooling to scale a small team's output — accelerating analysis, drafting and synthesis, and building repeatable workflows across many brands.

Brings a clear point of view on where AI adds leverage, and coaches the team to adopt it in daily work.

Strong ability to connect data insights to brand and portfolio strategy and outcomes.

Experience influencing stakeholders and shaping decisions through analytics.

Understanding of how marketing, product, and revenue dynamics interact.

Excellent communication skills, with the ability to present to senior stakeholders and executives.

Ability to translate complex analysis into clear, actionable insights and compelling narratives.

Proven ability to lead cross-functional initiatives and influence without authority.

Strong cross-functional partnership skills across Marketing, Product, Finance, Data Science, and PRISM.

Ability to operate effectively across many brands and markets in a high-ambiguity environment.