Data Scientist | Python | Machine Learning | SQL | Large Language Models | Hybrid, London
Our Mission
We’re on a mission to help blue-collar parts businesses grow and scale. These are the companies that keep the world running — powering the food we eat, the cars we drive, and the buildings we live in.
Historically, these businesses have been overlooked by the tech world, relying on outdated systems that make it hard to use their data effectively. Their information is often fragmented, unstructured, and inaccessible — meaning they can’t make the data-driven decisions that fuel modern growth.
With the rise of Large Language Models (LLMs), it’s now possible to bring this data together and make it understandable and actionable for non-technical users. Our team is leveraging these breakthroughs to empower every blue-collar business to grow with data.
We’re VC-backed by leading investors with a track record of supporting some of the world’s most successful startups.
The Role
We’re hiring a Research Data Scientist to join us at an exciting early stage. You’ll play a pivotal role in turning messy, real-world industry data into AI-driven insights and intelligent products.
Our customers operate in industries that have been underserved by modern software for decades. Their data is fragmented, incomplete, and complex — you’ll bring scientific rigor, creativity, and experimentation to make sense of it, test hypotheses, and build models that deliver measurable business impact.
This is a blend of data exploration, applied ML, and LLM experimentation. You’ll design and run experiments, validate ideas with real-world data, and collaborate closely with engineers to turn research into production-ready systems.
Key challenges you’ll help tackle:
- Transform large, messy datasets from legacy systems into structured, usable formats
- Design, run, and evaluate experiments using rigorous statistical methods
- Prototype ML models for forecasting, optimization, and recommendation across sales, inventory, and operations
- Explore and fine-tune LLMs for practical use cases within industry workflows
- Partner with engineers to take research from proof-of-concept to scalable production systems
- Build a culture of experimentation — documenting results, sharing learnings, and influencing product direction through data
You’ll work alongside experienced engineers and founders who are passionate about the intersection of AI, data, and real-world impact. This is your chance to shape the foundation of an AI platform for underserved industries — from raw data to tangible outcomes.
About You
- You see data as the engine for innovation — using it to uncover insights that drive business value
- You bring a scientific mindset (Bachelor’s/Master’s/PhD in a quantitative discipline) with strong experimental and statistical reasoning
- 2+ years of hands-on experience in data science, ML engineering, or applied research
- Skilled at designing and evaluating experiments with proper baselines, controls, and metrics
- Excited to explore and apply LLMs in practical, business-focused contexts
- Thrive in a fast-moving, iterative environment where research rapidly turns into real-world applications
- No domain expertise required — curiosity and adaptability are key
Technical skillset:
- Must-have: Python, data science/ML libraries (pandas, NumPy, scikit-learn, XGBoost, PyTorch, Hugging Face), experiment design, evaluation metrics
- Nice-to-have: LLM fine-tuning, prompt engineering, SQL/PostgreSQL
How We Work
- We live for our customers — aiming to be the most reliable, highest-ROI product they’ve ever used
- We move fast and stay focused on real-world results
- We tie every tech metric directly to user impact
- We’re open, collaborative, and challenge ideas — not people
- We take ownership — “that’s not my job” isn’t in our vocabulary
- We’re bold — transforming how an entire industry works isn’t easy, but we’re here for it
- We care deeply about our team and your growth — this should be the most enjoyable and impactful chapter of your career
Data Scientist | Python | Machine Learning | SQL | Large Language Models | Hybrid, London
