At A-Players, we are building a new AI product in the mental health and mindfulness space - and we are looking for a Data & Marketing Analyst who will own the analytics layer from day one.
We are not building analytics after the fact. We are building it before the first ad goes live. That means clean tracking from day one, attribution that reflects reality, and dashboards the performance team opens every morning - not once a quarter.
In practice, you will set up the full tracking infrastructure from scratch, own the attribution model, connect marketing spend to real revenue, and keep LTV and retention metrics current and trustworthy. You will work side by side with the performance marketing team.
You will be the dedicated analyst on this product. Around you is a mature data team of 10+ people across Data Analytics, Data Engineering, Data Science, BI, and AI, as well as shared infrastructure including BigQuery, dbt, Tableau, and GA4.
This role is a fit if you have navigated the full analytics stack at a fast-moving web subscription product, know what it takes to build trust in data from scratch, and want to do meaningful work on something that is just getting started.
Responsibilities:
- Build the web tracking foundation for the product. Set up GA4 and GTM, both client-side and server-side, from scratch: UTM conventions, dataLayer schema, event deduplication, and attribution windows.
- Implement server-side conversions for paid channels, including Meta CAPI, Google Enhanced Conversions, and TikTok Events API.
- Build and maintain a web attribution model that connects marketing spend to actual revenue, and deliver channel-level LTV and CAC analysis.
- Design and own Tableau dashboards for acquisition metrics, including CAC, ROAS, and channel mix; funnel metrics, including registration → first purchase → repeat purchase; retention metrics, including cohorts and LTV curves; and financial overview.
- Support the performance marketing team with ad-hoc SQL analysis and Python scripts for automation.
- Design and analyze A/B tests across the funnel, document results, and help drive action based on findings.
- Document tracking conventions and data definitions in the knowledge base.
What we look for:
- 3+ years of experience as a Data Analyst, Web Analyst, or Marketing Analyst working with web subscription or e-commerce products.
- Strong web analytics expertise, including funnels, attribution, tracking logic, and marketing performance measurement.
- Experience working with performance marketing data. Experience working with raw and semi-processed data from Facebook Ads, Google Ads, TikTok Ads, or similar platforms, including data validation and cleanup.
- Strong understanding of subscription business metrics, including LTV, cohorts, retention, recurring revenue, CAC, and payback period.
- Experience setting up web tracking from scratch at least once, for example for a new product, new funnel, or new market.
- Advanced SQL: window functions, CTEs, query optimization, and working with complex datasets.
- Proficient Python: pandas, NumPy, analysis scripts, and basic automation.
- Experience with BI tools such as Tableau, Looker, Power BI, or similar.
- Comfortable working with ambiguity and building structure where it does not yet exist.
- Open, clear, and proactive communication style.
- High level of ownership and initiative.
Nice to have
- Hands-on experience with GA4.
- Hands-on experience with GTM, including client-side and server-side implementation.
- Experience working with PSP data.
- A/B testing experience.
- Tableau experience: dashboards, calculated fields, parameter actions.
- BigQuery experience: large datasets, cost optimization, and performance optimization.
- Experience with dbt.
We offer:
- Full ownership and freedom to set up tracking from scratch for a new product, with no legacy constraints.
- Real business impact: you will work directly with a performance team running live campaigns, not build dashboards no one reads.
- A strong data team around you (10+people), including Data Engineers, Data Scientists, BI specialists, and AI specialists to consult with, learn from, and grow with.
- Modern stack: SQL, BigQuery, dbt, GA4, GTM, Tableau, and Python.
- Openness to new practices: the team has already implemented GrowthBook, dbt, server-side tracking, and GenAI skills for analysts.
- Career path: strong performance opens the door to real career growth.
- Flexible schedule and remote-friendly setup.
- Competitive compensation with regular performance reviews.
- Medical insurance.
- Learning and development budget.
