Job Description
The role
Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you!
You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh’s global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production.
To succeed in this role you should be curious, able to deal with uncertainty, 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, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally.
What you’ll do
- Join and become an integral part of a high-impact team covering menu personalization.
- Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.
- Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.
- Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
- Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.
- Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.
- Analyze the performance of our models to understand customer behavior, and come up with improvements.
- Contribute to a collaborative and knowledge-sharing environment.
What you’ll bring
- Proven track record of scientific work in your Bachelor’s, Master’s, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.
- Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
- In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.
- Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).
- Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.
- Experience with software development practices and tools (Git, CI/CD, Docker, AWS).
- 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.
- Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.
Interacting with product managers, UX designers, data and backend engineers, 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 and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders.
Above all, we are looking for people 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.
Let’s cut to the cheese, this is why you’ll love it here
- Box Discount- Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
- Health & Wellness- Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
- Vacation & PTO- Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance.
- Family Benefits- A parental leave top-up program for expectant parents.
- Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
- Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
- Diversity & Inclusion Initiatives- With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
- Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!
Flexible Hybrid Approach
At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience.
To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.
#LI-HYBRID
HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.
This is a posting for an existing vacancy. We are actively seeking to fill this position.
#DATA
Toronto, ON Pay Range
$140,000—$170,000 CAD
