Senior Data Analyst (SQL/NoSQL, Python)
About Trafilea
Trafilea is a Consumer Tech Platform for Transformative Brand Growth. We’re building the AI Growth Engine that powers the next generation of consumer brands.
With over $1B+ in cumulative revenue, 12M+ customers, and 500+ talents across 19 countries, we combine technology, growth marketing, and operational excellence to scale purpose-driven, digitally native brands.
We own and operate our own digitally native brands (not an agency), with presence in Walmart, Nordstrom, and Amazon, and a strong global D2C footprint.
Why Trafilea
We’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.
🚀 We build and scale our own brands.
🦾 We invest in AI and automation like few others in eCom.
📈 We test fast, grow fast, and help you do the same.
🤝 Be part of a dynamic, diverse, and talented global team.
🌍 100% Remote, USD competitive salary, paid time off, and more.
Key Responsibilities
The mission of the Data Analyst is to leverage data, computational science, and technology to deliver insights that enhance business performance. By combining statistical analysis, data visualization, and knowledge of population segments, this role guides the business in optimizing decisions, marketing performance, and strategic outcomes.
Support definition of project scope, objectives, and data requirements.
Deliver insights and recommendations to Marketing Acquisition and stakeholders.
Identify trends and growth opportunities through data interpretation.
Partner with Acquisition, Data Science, and Marketing to ensure analytical alignment.
Contribute to the design of methodologies for campaign testing, attribution, and econometric/statistical KPIs.
Work with BI teams to design and validate dashboards for digital performance.
Support A/B tests, lift tests, simulations, forecasting, and ad-hoc analysis.
Improve attribution/media mix methodologies through data analysis.
Prepare technical reports, briefings, and presentations.
Maintain clear documentation of acquisition methodologies and data science initiatives.