Scientific Data Specialist – Food Substances & Ingredients Ontology Data Expert

Must have:

• University degree (BSc/MSc) in biology, chemistry, biochemistry, microbiology, food science, pharmacy or a related field. You need to understand the chemistry and biology behind a regulation.
• 1–3 years in a job where accuracy of scientific or technical data mattered, e.g. laboratory, quality control, regulatory affairs or database curation.
• Advanced Excel with large files (tens of thousands of rows): lookups, pivot tables, Power Query, data validation, deduplication and text cleanup.
• Confident use of AI tools (ChatGPT, Claude, etc.) for data work, and the ability to spot when the AI gets it wrong.
• A structured mind: you understand categories and sub-categories, relationships, synonyms and unique identifiers, and you'd rather organise information than make long lists.
• Precision with scientific names: chemical names and identifiers (e.g. CAS numbers, E-numbers), Latin plant names, current classification of microorganisms.
• Fluent written and spoken English (B2+ minimum). It is our working language and the language of our data.

Nice to have:

• Familiarity with reference databases such as ChEBI, NCBI Taxonomy, FoodEx2, LanguaL or EuroFIR.
• Familiarity with the SKOS / OWL / RDF standards.
• Basic Python, SQL or regular expressions.
• Jira and Confluence.
• Knowledge of food law (Codex Alimentarius, EU law), or the willingness to learn it quickly.
• Other languages: French, German, Spanish, Portuguese, Italian, Arabic or Chinese.

You don't need to know regulations or ontologies on day one. We'll teach you. What we need is a solid scientific foundation and strong data skills.

About us
We are an international SaaS company. Our platform helps food producers check whether their products and labels comply with regulations in different countries. Our Data Team collects food regulations from official sources around the world and turns them into a structured database.

What is this role about?
The same thing often has different names in different countries and documents. For example, ascorbic acid, vitamin C and E300 are one substance. To match a rule from the EU, Brazil or China to a real product, we need one consistent "dictionary" of substances, ingredients, plants, microorganisms and product categories, with clear links between them. The technical term for this is an ontology. You will help build it and keep it accurate.

About 70% of your time goes into building and organising this dictionary. The other 30% is supporting work: matching new incoming data to it, quality checks and documentation. You'll use AI tools (Claude) every day, and you'll be the one who decides whether the AI's suggestions are scientifically correct.

We offer

• 100% remote work in an international team.
• B2B contract, [rate].
• Training in food regulations and data-structuring methods.
• Daily hands-on work with advanced AI tools.
• Real impact: within six months you become the team's second reference person for how the dictionary is built.

Please send your CV in English.

,[Create and define dictionary entries: substances, ingredients, plants, microorganisms, nutrients and product categories., Decide how they relate: groups (e.g. citric acid belongs to "acidity regulators"), sub-categories and equivalents between countries., Collect synonyms, translations and alternative names, so that different spellings lead to one entry., Remove duplicates and unclear entries. Every entry must be backed by an official source., Link data extracted from regulations to the right entries, and compare how different countries treat the same substance., Work with AI: ask it to propose new entries and standardise names, check its output critically and improve the prompts., Run consistency checks and document the rules you apply in the team's knowledge base (Confluence).] Requirements: Excel, AI, ChatGPT, Python, SQL, EU law