Senior Marketing Business Intelligence Analyst (all genders

The role

As a Senior Marketing Data Analyst in the Marketing Analytics team, you will play a key role in driving data-driven decision-making ed at our Global Headquarters in Berlin, you will own the Virality Analytics space, focusing on our Referral / Refer-a-Friend (RAF) programs across 12+ Hello Fresh markets and multiple brands (Hello Fresh, Factor, Green Chef, Chefs Plate, Every Plate, and more).

As a Senior Marketing Data Analyst in the Marketing Analytics team, you will play a key role in driving data-driven decision-making ed at our Global Headquarters in Berlin, you will own the Virality Analytics space, focusing on our Referral / Refer-a-Friend (RAF) programs across 12+ Hello Fresh markets and multiple brands (Hello Fresh, Factor, Green Chef, Chefs Plate, Every Plate, and more).

Referral is one of Hello Fresh's most efficient acquisition channels and a strategic growth lever for the next chapter of the business. You will be the analytical voice behind referral products, shaping how we measure them, how we grow them, and how we prove their value to the C-suite.

Your insights will shape strategies to optimize customer acquisition, sender engagement, friend conversion quality, and long-term customer value contribution from the referral channel.

• Act as the trusted analytics partner to the Virality Marketing, CRM, and Growth stakeholders — translating broad, ambiguous business questions into structured, prioritized analytical work
• Own the Virality marketing reporting (WBRs, QBRs and Forecasting) as well as funnel-level diagnostics across sender and friend journeys
• Represent Virality analytics in cross-functional forums with Product, Marketing, Data Engineering, CRM Ops, and Finance
• Co-design, quality-control, and analyze A/B tests on referral incentive structures, entry points, share flows and CRM comms
• Apply rigorous experimentation methodology — power analysis, primary metric selection, guardrail metrics, sample-size-aware interpretation — and communicate results to non-technical stakeholders
• Analyze customer value contribution using MPC2 predictions, sender-reward cost, friend-discount cost, and cost-per-conversion economics
• Contribute to virality-related initiatives beyond RAF — organic sharing, social loops, and future referral product bets
• Collaborate with fellow analysts across Marketing, Retention, Loyalty, and Product Analytics to keep methodology and definitions consistent
• Contribute to code reviews, dashboard reviews, and documentation
• Mentor more junior analysts on structured problem-solving and stakeholder communication

• 6+ years of experience in Marketing, Product, or Customer Analytics — ideally in a fast-paced B2C, subscription, or growth-oriented business
• Advanced SQL proficiency — comfortable with window functions, CTEs, complex joins, and performance-tuning queries on large event-level tables
• Strong hands-on experience with A/B testing design and analysis, including statistical significance, power, guardrails, and small-sample handling
• Proven ability to build and maintain BI dashboards (Tableau, Databricks, or similar) that reach senior leadership
• Experience designing and working with GenAI designed end to end workflows from problem definition to documentation and creating reproducible research
• Strong problem-solving skills with a track record of translating ambiguous business challenges into structured, data-driven projects
• Excellent stakeholder management skills, with experience influencing cross-functional Product, Marketing, and Engineering partners
• Comfort working with event-level behavioral data (Snowplow, Google Analytics, or equivalent) is a PLUS

• Prior experience with referral / virality / growth-loops programs, or with acquisition-channel economics (CAC, LTV, ROI)
• Experience with CRM analytics (email, push, in-app) — including deliverability, engagement, and unsubscription guardrails
• Python for data transformation, ad-hoc analysis, or lightweight modeling
• Familiarity with Databricks / Spark SQL, dbt, or similar modern data-stack tooling
• Exposure to statistical modeling techniques beyond A/B testing — segmentation, clustering,…