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&#39;ll play a pivotal role in driving data-informed pricing and discount decisions at HelloFresh. Based in our Berlin Headquarters, you&#39;ll help build best-in-class analytics to support price and discount strategy across HelloFresh&#39;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&#39;ll partner closely with the commercial Pricing &amp; Discount Strategy team and stakeholders across Product, Engineering, ML&amp;AI, and Finance. You&#39;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&#39;s room to grow into broader <strong>Market Insights</strong> work supporting senior leadership across our 15+ markets.</p> <h2>What You&#39;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&#39;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 brand and market performance and help inform Marketing budgets — contributing to the Market Insights agenda alongside senior stakeholders.</li> </ul> <h2>What You&#39;ll Bring</h2> <ul> <li>A <strong>motivated, collaborative mindset</strong> with strong team-working skills and a passion for solving complex business problems.</li> <li><strong>4+ years of experience</strong> in data science, analytics, or a related quantitative field — ideally in a fast-paced B2C or subscription business.</li> <li><strong>Strong SQL and Python</strong> (required) — you&#39;re comfortable owning an analysis end to end.</li> <li>A foundation in <strong>experimental design and A/B testing</strong>, including how to size a test and choose primary and guardrail metrics.</li> <li>Working knowledge of <strong>causal inference and econometrics</strong> — price elasticity, incrementality, and quasi-experimental methods.</li> <li>Solid <strong>applied statistics</strong>, and familiarity with common <strong>machine-learning</strong> methods (regression, trees, clustering; uplift / heterogeneous-effects a plus) — with the judgment to know when a method genuinely helps and when a simpler approach is better.</li> <li>A strong understanding of <strong>Marketing and Growth metrics</strong> and how they connect to overall business pe