Senior Marketing Analyst

Twin Health

At Twin Health, we empower people to improve and prevent chronic metabolic diseases, like type 2 diabetes and obesity, with a new standard of care. Twin Health is the only company applying AI Digital Twin technology exclusively toward metabolic health.

We start by building a dynamic model of each person’s metabolism — drawing on thousands of data points from CGMs, smartwatches, and meal logs — that maps their personal path to better health. Guided by a dedicated clinical care team, our members have lowered their A1C below the diabetes range, achieved lasting weight loss, and reduced or even eliminated medications, all while living healthier, happier lives.

Working here

Our team at Twin Health is passionate, talented, and united by a shared purpose: to improve the metabolic health and happiness of our members. We believe in empowering every Twin to make a meaningful impact for our members, our clients, and each other, while enjoying a supportive, collaborative work environment.

Twin has been recognized not only for our innovation but also for our culture, including: Innovator of the Year by the Employer Health Innovation Roundtable (EHIR), selected to CB Insights’ Digital Health 150, and named one of Newsweek’s Top Most Loved Workplace® .

With more than $100 million raised in recent funding, including a $53 million Series E round in 2025 led by Maj Invest, and a $50 million investment in 2023 led by Temasek, Twin is scaling rapidly across the U.S. and globally. Backed by leading venture firms like ICONIQ Growth, Sequoia, Sofina, Temasek, and Peak XV, we are building the most impactful digital health company in the world.

Join us as we reinvent the standard of care in metabolic health.

Opportunity

We are looking for a Senior Marketing Analyst to own measurement and insight across our marketing channels — email, direct mail, and digital. This role sits at the intersection of marketing strategy, data, and technical execution, turning raw campaign and behavioral data into clear, actionable analysis that drives decisions at every level, from channel owners to the executive team.

You will serve as the analytical backbone of the marketing organization — defining how we measure performance, designing and reading experiments, building the data models behind our reporting, and translating complex analysis into recommendations leadership can act on. You will partner closely with channel owners, data engineering, finance, and product to align on attribution, measurement standards, and the metrics that matter most.

This is a hands-on, high-impact individual contributor role for someone with the experience and technical expertise to function successfully and independently in a complex, fast-moving environment — someone who is equally comfortable writing SQL against a warehouse, debugging a tracking tag, and presenting an in-depth analysis to senior leaders.

Responsibilities

Channel Performance Measurement Analytics

Measure and report on performance across email, direct mail, and digital — defining the right metrics, building reporting, and surfacing what is working and what is not

Own digital analytics end to end, including event tracking and tagging strategy, and partner with engineering to ensure data is captured accurately across web and app properties

Build and maintain attribution and marketing mix models to quantify channel contribution and guide budget allocation across the marketing portfolio

Analyze paid channel performance — spend efficiency, ROAS, and incrementality — and translate findings into clear optimization recommendations

Data Science Advanced Modeling

Own marketing mix modeling (MMM) end to end — building, validating, and refreshing models that quantify channel contribution, diminishing returns, and saturation to guide budget allocation

Develop propensity models to predict member behavior — conversion, churn, and engagement — and operationalize scores to drive targeting, segmentation, and lifecycle marketing

Apply Bayesian network analysis and related probabilistic methods to model relationships between marketing drivers and outcomes, quantify uncertainty, and support causal and incrementality analysis

Partner with data engineering to productionize models, monitor performance over time, and ensure outputs are reliable, explainable, and decision-ready for leadership

Experimentation Testing

Design, run, and analyze A/B and multivariate tests, ensuring sound experiment design, statistical rigor, and clear interpretation of results

Establish testing standards and a roadmap of experiments that continuously improve channel and campaign performance

Data Modeling Engineering

Build and maintain reliable, well-documented data models in Snowflake using dbt and SQL that the marketing team can trust for reporting and analysis

Connect and integrate data from martech and ad platforms via APIs to bring sources together into unified, analysis-ready datasets

Insights Communicatio…