# Staff Data Scientist at HelloFresh > United Kingdom · Staff · Analytics / Data science · open. Source: https://alderhq.app/jobs/greenhouse%3Ahellofresh%3A8280296 (read 2026-11-04). ## Facts (observed) - Company: [HelloFresh](https://alderhq.app/companies/hellofresh) - Location text: Sydney, New South Wales, Australia; Sydney, Australia - Where it can be done from (inferred): United Kingdom (evidence: "Location: Sydney, New South Wales, Australia; Sydney, Australia") - Posted: 2026-10-14 (20 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://careers.hellofresh.com/global/en/job/8280296?gh_jid=8280296 - Skills listed (inferred): Python ## Pay and sponsorship - Posted pay: not posted - H-1B filings at this company for similar roles, FY26: 1 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) ## Description (the employer's text) ### 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 --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Ahellofresh%3A8280296 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.