Staff Data Scientist
hellofresh
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2,681 open scientist roles across 399 companies are on ApplySarthi right now, most of them in Bengaluru (139), Hyderabad (77), Delhi NCR (29).
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What scientist roles keep asking for: Python (63%), Machine learning (51%), SQL (30%), LLMs (20%), Deep learning (18%), R (18%), C++ (17%), Generative AI (15%) — counted across their open postings here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for scientist roles keep coming back to Python, Machine learning, SQL, LLMs. Practise those questions before you sit with hellofresh.
Questions you are likely to be asked
- Why do you want to join hellofresh?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
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Practise the Staff Data Scientist at hellofresh interview free →Job Description
As the Staff Data Scientist, you will lead and develop a high-performing data science team, translating complex business challenges into scalable analytical and machine learning solutions that drive measurable commercial outcomes across HelloFresh's brands.
This role is based in Chippendale, Sydney (hybrid working environment) and reporting to the Director Data ANZ.
You will…
- Build and develop the data science team by providing technical mentorship, regular coaching, and stretch opportunities.
- Partner with senior stakeholders across commercial, product, and operations to shape the data science roadmap and communicate progress and outcomes clearly.
- Drive delivery of high-impact projects including ML models, experimentation frameworks, and analytical solutions.
- Maintain technical depth by contributing to hands-on work, including reviewing code, validating modelling approaches, and ensuring technical rigour.
- Champion best practices in experimentation (A/B testing), model development, and deployment.
- Manage and prioritise the team's roadmap, balancing strategic initiatives with BAU demands.
- Recruit and retain data science talent, contributing to a collaborative culture.
You have…
- Demonstrated experience leading or managing data science teams with a track record of developing talent and delivering end-to-end projects.
- Strong hands-on background in Python and PySpark, with experience in Databricks or equivalent cloud-based data platforms.
- Experience with traditional data science tools and techniques, such as XGBoost and deep learning frameworks.
- Deep knowledge of A/B testing methodology and machine learning model development, validation, and production deployment.
- Prior experience as a practicing data scientist capable of engaging credibly at a technical level.
You are…
- An influential partner capable of translating ambiguous business problems into clear data science briefs for senior stakeholders.
- A mentor who values curiosity, technical rigour, and continuous improvement within a team.
- Driven by commercial impact, retention, acquisition, and operational efficiency.
- Familiar with deep learning frameworks and their practical business application (desirable).
What you’ll get in return…
- The chance to have a significant impact in a leading global food technology company
- Flexible working arrangements
- Egoless environment, constant learning with room for personal growth
- Free access to Headspace
- HelloFresh Academies - internal learning & development
- A diverse and vibrant international environment, with offices in 18 countries
- Company discount - 70% off HelloFresh & 40% off Youfoodz
Start Date: Immediately available - Can wait a notice period
Duration: Permanent full time role
Location: Chippendale Head Office - hybrid working environment
Salary: Competitive salary & employee benefits
#LI-Hybrid
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Listed on arbeitnow · posted 2026-10-16. ApplySarthi collects openings and links to application pages; the role is advertised by hellofresh, not by us.