Senior Marketing Data Analyst Pricing (all genders)

<h2>The role</h2> <p>As a <strong>Senior Marketing Data Analyst</strong> on our <strong>Pricing Analytics</strong> team within the Global <strong>Marketing Analytics</strong> organisation, you'll play a pivotal role in driving data-informed pricing and discount decisions at HelloFresh. Based in our Berlin Headquarters, you'll help build best-in-class analytics to support price and discount strategy across HelloFresh's brands — turning data into strategic recommendations, challenging the status quo, and directly shaping how our global brands price, grow, and operate.</p> <p>Reporting to the Associate Director of Pricing Analytics, you'll partner closely with the commercial Pricing &amp; Discount Strategy team and stakeholders across Product, Engineering, ML&amp;AI, and Finance. You'll bring the toolkit of a data scientist — experimentation, causal inference, and modeling — and the judgment to turn it into decisions. As our scope expands, there's room to grow into broader <strong>Market Insights</strong> work supporting senior leadership across our 15+ markets.</p> <h2>What You'll Do</h2> <ul> <li><strong>Own price and discount experiments end to end</strong> — frame the hypothesis, design the test, size it, launch it through our always-on testing program, and deliver the readout.</li> <li><strong>Model how customers respond to price and promotions</strong> — price elasticity, geo-segmented pricing, discount and promo effects, and ML-assisted discount recommendations.</li> <li><strong>Apply causal inference</strong> — incrementality and quasi-experimental methods (difference-in-differences, synthetic control, matching) — to measure true impact where a clean A/B test isn't possible.</li> <li><strong>Ship analysis as data products</strong> — production pipelines and self-serve apps (Databricks, SQL, Python, Streamlit) that stakeholders use directly, not one-off notebooks.</li> <li><strong>Build and enhance reporting and visualization assets</strong> that support day-to-day pricing decisions and strengthen performance oversight.</li> <li><strong>Communicate complex technical findings</strong> as clear recommendations and tangible next steps for commercial leaders without a technical background.</li> <li><strong>Collaborate with data science, finance, and marketing</strong> to measure discount impact consistently across gross and net revenue and short- and long-term customer profitability.</li> <li><strong>Collaborate with and mentor analysts</strong> within the team, championing scalable, automated, and reproducible ways of working.</li> <li><strong>As scope grows</strong>, measure, benchmark, and monitor