At a Glance
- Tasks: Explore complex datasets and build innovative models for a cutting-edge AI project.
- Company: Join a top-employer with a strong culture of empathy and trust.
- Benefits: Enjoy paid vacation, sick leave, and regular team-building activities.
- Other info: No chemistry background needed; domain expertise provided by the team.
- Why this job: Make a real impact in an exciting startup environment with growth opportunities.
- Qualifications: Proven experience in shipping models, strong Python skills, and independent mindset.
The predicted salary is between 59400 - 72600 £ per year.
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
Senior Data Scientist (Contract · London) employer: Djinni
Join a top-employer company renowned for its strong culture of empathy, trust, and openness, where your contributions as a Senior Data Scientist will be valued and impactful. Located in London, this role offers a unique opportunity to work on an innovative AI project within a supportive environment that prioritises employee well-being and growth, alongside regular team-building activities and paid leave. Embrace the chance to set standards in a dynamic startup atmosphere while collaborating with a dedicated team focused on meaningful advancements in the chemicals and materials economy.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist (Contract · London)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Djinni!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Djinni.
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When you find a suitable opening like Senior Data Scientist (Contract · London) at Djinni, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist (Contract · London)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Djinni, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Djinni. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Djinni
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Djinni!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
