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.
Warszawa, Masovian Voivodeship, Poland
Live, first seen by us 23 days agoDesign, build, and own statistical and ML models from data collection to production
Design experiments, define success metrics and guardrails, and interpret results under uncertainty
Monitor models in production for performance, data reliability, and drift
Retrieve and analyze large datasets and build the pipelines models depend on
Coach junior data scientists and help solve problems as they arise
Design, build, and take ownership of statistical and machine learning models, from data collection through to production
Experimentation: design tests, define success metrics and guardrails, and interpret results while accounting for statistical uncertainty, noise, and bias.
monitor model performance, data reliability, and drift once in production
Retrieve, manipulate, and analyze large, heterogeneous datasets, and build the data pipelines your models depend on.
support and coach more junior data scientists
What you’ll bring: The Ingredients - Proven track record of scientific work through a Bachelor’s, Master’s, or PhD in statistics, physics, economics, mathematics, data science, or a related quantitative field. - 3+ years of professional experience as a (senior) data scientist or in a related quantitative role, ideally in e-commerce, marketing, or a comparably high-traffic, consumer-facing environment.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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.
- Strong marketing and/or growth domain knowledge, with experience applying statistical models such as regressors and classifiers, and interpreting experiment results under real-world uncertainty. - Fluency in Python and its scientific stack (NumPy, Pandas, Scikit-learn, Matplotlib); comfortable retrieving and analyzing data with SQL. Experience with Databricks/Spark is a plus. - Familiarity with software engineering practices and tools (Git, Docker, AWS or similar cloud environments).
- Fluency in Python and its scientific stack (NumPy, Pandas, Scikit-learn, Matplotlib); comfortable retrieving and analyzing data with SQL. Experience with Databricks/Spark is a plus. - Familiarity with software engineering practices and tools (Git, Docker, AWS or similar cloud environments). - Comfortable using recent Gen AI tools (e.g. Claude Code) to design and build solutions in a structured and pragmatic manner.
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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.
Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.
Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.
HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.
The Growth Alliance powers HelloFresh’s marketing engine, from media investment and in-channel optimization, to the conversion funnel, to how and when we communicate with customers. As a Senior Data Scientist, you will design and ship statistical and machine learning models that turn data from experiments, campaigns, and customer behavior into decisions that directly move the business: how we spend our marketing budget, how we convert visitors into customers, and how we personalize every touchpoint along the way.
You’ll join one of several teams within the alliance, spanning marketing measurement and attribution, channel optimisation, funnel optimisation and decisioning on customer communications and messaging. Across all of these topics, the through line is the same: rigorous modeling, close collaboration with engineering and marketing stakeholders, and a bias toward shipping models that work in production, not just in a notebook.
To succeed in this role, you should be a curious, pragmatic problem solver who relentlessly prioritizes based on impact, is comfortable with statistical uncertainty, and can translate a fuzzy business question into a concrete, testable model.
At HelloTech, flexibility and cross-functional collaboration are core to how we work. While this role is aligned to a specific Alliance, strong candidates may also be considered for opportunities across different teams or projects.
Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.
Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you. We aim to review your profile and respond within 5 business days.
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Warszawa, Masovian Voivodeship, Poland
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