Senior Data Analyst, Marketing (SheMed)

eMed•Miami, FL

2d•Onsite

About The Position

At SheMed, our mission is to revolutionize women’s health by providing accessible and personalized solutions tailored specifically for women. We are a startup consisting of enthusiastic people who are committed to empowering women with the knowledge and tools they need to take control of their health and well-being. SheMed is an innovative and advanced weight loss program that is groundbreaking in the world of women’s health. We have an unwavering dedication to quality care, and strive to create a supportive and compassionate community where every woman can thrive and achieve optimal health. In doing so, we believe SheMed will be a strong force in closing the women’s health gap. We are seeking a highly analytical, commercially minded Senior Data Analyst, Marketing to become a key partner to the marketing team at SheMed. This role will be embedded within marketing, helping the team make smarter, faster, data-led decisions across acquisition, retention, customer journeys, and campaign performance. You will drive the measurement of key growth channels, including Meta, Google, and influencer partnerships, and provide clear insight into what is working, what is not, and where we should focus next. You will play a critical role in connecting marketing behaviour with wider business performance, including subscription metrics, customer acquisition cost, lifetime value, and retention. The ideal candidate combines strong technical expertise with excellent commercial judgement and communication skills. You should be comfortable working with complex datasets, but equally confident translating your analysis into clear, non-technical narratives for senior leadership.

Requirements

3–5+ years of experience in marketing analytics, growth analytics, commercial analytics, or a similar data-focused role.
Experience working in a high-growth, fast-paced environment, ideally within D2C healthcare, subscription, consumer health, wellness, ecommerce, or a startup environment.
Strong experience analyzing paid marketing performance across channels such as Meta, Google, paid search, paid social, influencer, affiliates, or CRM.
Experience owning and reporting on subscription or customer growth metrics, such as CAC, LTV, retention, churn, payback period, and cohort performance.
Advanced SQL skills and experience working with large, complex datasets.
Experience using dbt for data transformation, modeling, testing, and documentation.
Strong Tableau experience, including building dashboards for senior stakeholders and non-technical users.
Experience using Python or R for advanced analysis, predictive modeling, forecasting, or statistical modeling.
Ability to translate complex datasets into clear, non-technical narratives that influence senior decision-making.
Excellent communication, presentation, and stakeholder management skills.

Nice To Haves

Experience with Marketing Mix Modelling or incrementality testing
Experience with PostHog, Braze, or similar product analytics and CRM platforms
Experience working with clinical, health, patient, or outcomes data

Responsibilities

Own marketing performance measurement across channels including Meta, Google, paid social, affiliates, and influencer partnerships.
Develop attribution frameworks to evaluate acquisition, conversion, retention, and revenue performance.
Partner with marketing teams to optimise campaigns, audience targeting, creative performance, and budget allocation.
Analyse the end-to-end customer journey to identify drop-off points, behavioural trends, and growth opportunities.
Deliver insights to improve conversion, onboarding, CRM, lifecycle communications, retention, and customer value.
Own reporting and analysis for key subscription KPIs including CAC, LTV, payback period, churn, retention, conversion rate, subscription growth, and channel ROI.
Apply advanced analytics using SQL, Python, or R for cohort analysis, forecasting, predictive modelling, and Marketing Mix Modelling.
Build and maintain dashboards and self-serve reporting in Tableau to support data-driven decision-making.
Translate complex analysis into clear, actionable recommendations for senior stakeholders.
Use SQL and dbt to develop trusted, scalable data models and analytics infrastructure.
Collaborate with data, marketing, product, medical, finance, and leadership teams to align insights with business priorities.
Support analysis of customer engagement and health outcomes in partnership with clinical and product teams.
Proactively identify opportunities, challenge assumptions with evidence, and help teams move from data to decisions.