Company: Djinni
Location: London
Job Description:
We are looking for a Senior Data Scientist to join a seed-stage AI project on a full-time contract basis (2–3 months, with possible extension or transition to a permanent role). The project is building a computable model of the global chemicals and materials economy.
This is a hands-on role — you will be setting the standard, not following one.
Location: London, hybrid (priority) Start: ASAP Format: Contract, full-time, 2–3 months
Your responsibilities will include:
- Profile and explore complex real-world industrial datasets — chemical plants, supply chains, material grades
- Build baselines, then define evaluation sets and metrics before modelling
- Ship classifiers and matching/inference models with measured error rates and written error analyses
- Use LLMs where they genuinely belong — extraction, constrained labelling, code generation — with proper evals, never open-loop guessing
- Document model decisions, failure modes, and validation approaches clearly
What we expect from you:
- Proven track record of shipping models to production where being wrong had real consequences — and ability to explain exactly how they were validated
- Strong Python — pandas, scikit-learn, solid statistical instincts
- Ability to define evaluation frameworks and metrics independently, not just implement someone else’s
- An independent operator mindset — comfortable setting standards in an early-stage environment
- Experience building LLM pipelines with real evaluation harnesses is a strong plus
- No chemistry background needed — domain expertise is provided by the team
Soft skills / Mindset:
- Rigorous — defines what “good enough” means before building, not after
- Communicates clearly — can explain model decisions, tradeoffs, and failure modes to a non-technical audience
- Fast — comfortable with startup pace and ambiguity
- Honest about uncertainty — flags unknowns early rather than papering over them
What We Offer:
- Work at a Top-employer company (according to DOU 2025)
- A strong culture built on empathy, trust, openness, and real care for employees
- Paid vacation and sick leave
- Team events and regular team-building activities
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Posted: August 20th, 2026
