Time since we first saw it
Day 23
Similar jobs usually come down between day 7 and day 56.
At HelloFresh, jobs usually come down by about day 49.
From 10,194 similar postings that came down, and 33 of HelloFresh’s. Coming down is not always a hire.
Reads like a Data Scientist role: models and experiments.
Berlin, Berlin, Germany
Live, first seen by us 23 days agoOwn price and discount experiments from hypothesis to readout
Model price elasticity and discount/promo response, including ML-assisted recommendations
Apply difference-in-differences, synthetic control and matching to measure impact
Ship analysis as production pipelines and self-serve apps, not one-off notebooks
Translate technical findings into recommendations for non-technical commercial leaders
Own price and discount experiments end to end
Model how customers respond to price and promotions
Apply causal inference
Ship analysis as data products
Communicate complex technical findings
4+ years of experience
Strong SQL and Python (required)
A foundation in experimental design and A/B testing
Working knowledge of causal inference and econometrics
Excellent communication skills in English
From the employer’s posting.
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Day 23
Similar jobs usually come down between day 7 and day 56.
At HelloFresh, jobs usually come down by about day 49.
From 10,194 similar postings that came down, and 33 of HelloFresh’s. Coming down is not always a hire.
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Apply causal inference — incrementality and quasi-experimental methods (difference-in-differences, synthetic control, matching) — to measure true impact where a clean A/B test isn't possible. - Ship analysis as data products — production pipelines and self-serve apps (Databricks, SQL, Python, Streamlit) that stakeholders use directly, not one-off notebooks. - Build and enhance reporting and visualization assets that support day-to-day pricing decisions and strengthen performance oversight.
- 4+ years of experience in data science, analytics, or a related quantitative field — ideally in a fast-paced B2C or subscription business. - Strong SQL and Python (required) — you're comfortable owning an analysis end to end. - A foundation in experimental design and A/B testing, including how to size a test and choose primary and guardrail metrics.
- A strong understanding of Marketing and Growth metrics and how they connect to overall business performance. - Comfort in a modern data stack (Databricks / Spark / a SQL warehouse) and a visualization tool (Tableau, Looker, or Power BI; or apps built in Streamlit). - A results-oriented, structured approach, able to turn vague or ambiguous business questions into clear analytical frameworks and insights.
- Bayesian or hierarchical / mixed-effects modeling. - GenAI / LLM tooling for analytics (e.g., natural-language-to-SQL, agent or assistant surfaces). What we offer
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New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
As a Senior Marketing Data Analyst on our Pricing Analytics team within the Global Marketing Analytics 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.
Reporting to the Associate Director of Pricing Analytics, you'll partner closely with the commercial Pricing & Discount Strategy team and stakeholders across Product, Engineering, ML&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 Market Insights work supporting senior leadership across our 15+ markets.
Nice to have:
Elevate your lifestyle! Join one of Europe's fastest-growing tech powerhouses in a dynamic phase of expansion.
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Berlin, Berlin, Germany
- Immerse yourself in a diverse global community of 90+ nationalities. - Enjoy a competitive compensation package that goes beyond the norm, with perks like a HelloFresh-subsidized Pension Scheme, Berlin relocation support, and a Hybrid working model. - Exclusive discounts on your weekly HelloFresh box and office meals.
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