Lead Marketing Data 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

marketing channels: email, direct mail, and digital. This role sits at the intersection of marketing strategy, data, and technical execution. You will turn raw campaign and behavioral data into clear analysis that drives decisions at every level, from channel owners to the executive team.

Right now, the first priority is to understand performance before we optimize it. In your first year you will establish trusted, consistent performance baselines across channels, find where the data does not add up, and tell us what is working and what is not. As that foundation matures, the role grows into attribution, marketing mix, and scoring models that guide budget allocation and targeting.

Our data foundation is built by our data engineering team. You will be its most demanding user. You will query across sources to answer marketing questions, find the gaps and inconsistencies others miss, and tell the data team what needs to be tracked, modeled, or fixed so the next question is easier to answer.

This role is for someone whose edge is judgment. You know what to ask before you write the query, you notice when an answer does not add up, and you give the marketing team a recommendation they can act on. It is a hands-on, high-impact individual contributor role for someone who works independently in a fast-moving environment and is equally comfortable digging through a warehouse and presenting 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

Decision support for performance marketing

Partner with channel owners to turn campaign goals into specific, testable questions, and answer them with analysis before launch, while campaigns are in flight, and after they close

Analyze channel mix, budget allocation, and pacing using CPM, CPC, CAC, conversion rate, and ROAS, and recommend where to shift spend

Profile audiences across multiple data sources to size and describe segments for targeting, and recommend who to reach and with what message

Analyze funnels and landing page performance from impression through registration to enrollment, and recommend conversion rate improvements

Data quality and the data foundation

Write complex SQL to explore, join, and reconcile data across the warehouse and martech platforms, and validate queries drafted with AI assistance

Question the data: find gaps, conflicting definitions, and tracking breaks, reconcile numbers across platforms, and raise issues with the specifics the data team needs to fix them

Define requirements for data engineering, including the events, facts, dimensions, and metric definitions needed to support attribution, mix modeling, and scoring in the future, and explain why each one matters

Document the metric definitions and logic the marketing team relies on

Data Science & Advanced Modeling

These responsibilities build on the measurement foundation above. Expect to start by evaluating and directing this work, and to take on more of the build as the data matures.

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 and other scoring 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 and testing

Design, run, and read A/B and multivariate tests, including sample sizing, significance, and interpretation, and recommend what to test next

Help establish testing standards and maintain a prioritized roadmap of experiments

Insights and communication

Present findings and recommendations to marketing leadership and the executive team in a clear, decision-ready way

Partner with marketing, engineering, data engineering, finance, and product to align on definitions, attribution, and measurement standards

Other duties as assigned

Qualifications

8+ years in marketing analytics, performance marketing analytics, data analytics, or a closely related field

Sound analytical judgment, shown by examples where you reframed a question, found a flaw in the data, or changed a decision

Proven experience measuring email, direct mail, and digital marketing performance, including channel mix, budget allocation, CPM, CAC, ROAS, and conversion rate optimization

Comfort writing and validating complex SQL against a cloud data warehouse (Snowflake preferred), with or without AI assistance. Data engineering is not part of this role.

Working knowledge of attribution, marketing mix modeling, incrementality, and paid channel analysis

Experience with scoring and predictive models, such as propensity models, marketing mix models, or Bayesian methods, and with applying them to real marketing decisions. Depth in at least one of these and a working understanding of the others.

Working knowledge of tracking and instrumentation (UTMs, pixels, tag managers, event taxonomy) and of data modeling concepts such as facts and dimensions, enough to specify requirements and spot problems

Solid understanding of A/B testing: experiment design, sample sizing, significance