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Salary
$74k – $116k per year
Location
In office (Warsaw)
Seniority
Senior · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
We are the world's leading integrated food solutions provider, operating in 16 geographies with a portfolio of 8 brands that offer meal kits, ready-to-eat meals, and specialty products such as pet food and high-quality meat & seafood. We have built not one but two multi-billion-euro business segments, meal kits and ready-to-eat, proving our ability to scale globally with precision and profit. Our 40 offices & distribution centers are across the world, and we employ around 18,000+ people globally.

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.

About the role: What's in the Box

Do you consider yourself to be a Demand Forecasting Model expert and enthusiast? Then this position might be the perfect fit for you!

As a Senior Data Scientist, Demand Forecasting, you will play a pivotal role in designing, implementing, and improving our demand forecasting time series and causal models that are used across HelloFresh's global markets. In this role, you can expect to have a large and tangible impact on our global supply chain. You will work closely with forecasting data scientists and machine learning (ML) engineers, together delivering statistical and ML models to production.

To succeed in this role you should be curious, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, prioritizing tasks based on effort and potential impact, as well as use GenAI tooling to boost your productivity. As a senior member of the Data Science team, you will jump into problem solving with others as challenges arise, and coach junior members of the team to develop their skills and increase their impact. Your team will be a place where your thoughts and opinions matter, and your contributions will have a tremendous impact on the team's success.

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.

What you'll do: The Recipe

  • Join and become an integral part of a high-impact data science team covering the global demand forecasting domain.

  • Take technical ownership of our demand forecasting time series and causal models from data collection to operationalization and closely align them with non-technical stakeholders.

  • Shape and transform the future of demand forecasting at HelloFresh by proposing new approaches and evolving the statistical and ML models in pace with future company strategies.

  • Experiment and explore opportunities to constantly improve and refine the approaches.

  • Work with state-of-the-art technologies - such as AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, and Databricks - for the full ML lifecycle, from experimentation to production deployment

  • Collaborate closely within cross-functional teams (product, demand planning, engineering) to translate business objectives into concrete, data-driven strategies.

  • Think out of the box to come up with new ways of how we can improve the forecast we deliver to our stakeholders.

  • Mentor and support data scientists and colleagues, fostering a collaborative and knowledge-sharing environment.

What you'll bring: The Ingredients

  • Proven track record of scientific work in your Bachelor's, Master's, or PhD in econometrics, statistics, computer science, physics, economics, mathematics, data science or similar.

  • Long-term (3+ yrs) work experience as a (senior) data scientist in demand forecasting, developing time series and causal models.

  • Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib, etc. (experience in Databricks and PySpark is a plus).

  • In-depth knowledge of how to handle statistical uncertainties and how to apply statistical models such as regressors and classifiers.

  • Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.

  • Comfortable working in cloud-based environments for data science (AWS, GCP, or Azure) - beyond local notebooks, with experience deploying and running ML workloads on shared infrastructure.

  • Experience collaborating through Git and code review workflows.

  • Ability to describe a GenAI-supervised development flow - where AI tools (e.g., Claude Code, Cursor) handle code generation, execution, output analysis, and iteration, with the data scientist acting as supervisor and decision-maker. Hands-on experience is a plus, but a concrete vision is a must.

  • You love to learn, are a critical thinker and creative problem solver who strives for excellence.

  • You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.

  • Exceptional communication and collaboration capabilities.

  • Proficiency in using GenAI tooling to boost productivity and the development workflow.

  • Strong supply chain domain knowledge is a big plus.

Interacting with demand planners, ML and data engineers, product managers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling skills to a wide range of business problems in the forecasting space while also acting as an ambassador to coach team members and stakeholders.

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.

What we offer: The Toppings

  • Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech's international teams, in a culture of active knowledge sharing.

  • Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.

  • Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.

  • End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.

  • Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

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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