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, and interpretation
• Experience using AI tools such as Claude in analysis and reporting workflows
• Excellent communication skills, with a track record of presenting analysis to senior leadership
• This remote opportunity is based out of the U.S. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Preferred

• Agency, e-commerce, startup experience
• Experience with a marketing or product analytics platform (e.g., GA4, Amplitude, Adobe Analytics)
• Familiarity with incrementality measurement and experimentation platforms
• Experience with SQL, Python or R for analysis
• Experience with a BI tool such as Lightdash, Looker, or Tableau, and familiarity with dbt
• Marketing experience in healthcare or another regulated industry
• This remote opportunity based out of the U.S. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Compensation and Benefits  

The compensation range for this position is $145,000 - $165,000 annually. 

Twin has an ambitious vision to empower people to live healthier and happier lives, and to achieve this purpose, we need the very best people to enhance our cutting-edge technology and medical science, deliver the best possible care, and turn our passion into value for our members, partners and investors. We are committed to delivering an outstanding culture and experience for every Twin employee through a company based on the values of passion, talent, and trust. We offer comprehensive benefits and perks in line with these principles, as well as a high level of flexibility for every Twin

• A competitive compensation package in line with leading technology companies
• A remote and accomplished global team
• Opportunity for equity participation 
• Unlimited vacation with manager approval
• 16 weeks of 100% paid parental leave for delivering parents; 8 weeks of 100% paid parental leave for non-delivering parents
• 100% Employer sponsored healthcare, dental, and vision for you, and 80% coverage for your family; Health Savings Account and Flexible Spending Account options
• 401k retirement savings plan