About us
We're a market leading tech company that source, extract and package data to create the ultimate private company database for the UK and, as of recently, Germany too. Through a combination of people power and machine learning, our platform helps 20+ different industries invest in, understand, and partner with these exciting businesses.
We're at a pretty exciting stage right now - we've built a profitable, high-growth business, with 140+ employees and an enviable client list. But we're not done yet. We're on a mission to become a global data company that helps every organisation discover, understand, and work better with the UK's private companies. (read more about our exciting engineering team on our dedicated notion page)
The role
Our Machine Learning team is expanding into three key areas: [1] enabling us to significantly expand the depth and breadth of our data, [2] empowering our Data Team to handle this expansion, and [3] building tools that help our customers make better data-driven decisions.
Day-to-day your responsibilities might include:
- Research & Evaluation:Understand the specifics of a business requirement and assess whether it could be improved by a data product or machine learning solution.
- Develop Proofs of Concept:Start with a problem, investigate possible solutions, and create a proof of concept to assess whether it can be solved with the resources we have.
- Production & Development:Craft a data product, machine learning model or algorithm that can be put to use with the rest of our platform; then maintain and document it.
- Monitor:Ensure that the production systems are continuously delivering value accurately and efficiently.
- Communicate and Mentor:Share findings, ideas, risks, successes, and failures with colleagues with a variety of technical skills levels.
About you
There is no one size fits all for this role, but we'd expect you have at least 3 years experience with programming preferably Python. You could be any of the following:
Technical must haves:
- Proven experience in training, evaluating and deploying machine learning models.
- Solid understanding of data science and machine learning concepts.
- Experience with some machine learning/data engineering tech in Python (such as numpy, pytorch, pandas/polars, airflow, etc).
- Experience developing data products using large language model, prompt engineering, model evaluation.
- Experience with web services and programming (such as Python, docker, databases, etc).
Great to (but not essential):
- Master's or Ph.D. in Computer Science, Machine Learning or a related field.
- Understanding of some of the following: FastAPI, PostgreSQL, Celery, Docker, AWS, Modal, git, continuous integration.
Ideally you'll be:
- Curious & self-motivated - you like to learn new skills independently and apply them to your work. You care about the methodologies, tooling, and technology in machine learning and data science.
- Creative - you think of innovative, unusual, smart and efficient ways of tackling data problems. You're able to connect information from multiple sources or disciplines to come up with ideas on how to solve them.
- Empathetic - You get into the shoes of the person experiencing a problem that you might be able to solve and use that to communicate to them effectively.
Our offer
We're offering a competitive starting salary.
On top of this, we invest a lot in keeping our people happy and healthy! So as well as that, you'll also get:
- Professional development:Ongoing training and development, and free books.
- A stake in the company:Substantial options scheme, so you can share in the growth that you help create.
- The latest tech:We'll provide you with all the tech you need to be productive (including a Mac!), whether you're in the office or working from home.
- Health and wellness:Free counselling, wellbeing baskets, and healthy snacks.
- Events:Drinks every Friday, interesting talks from industry experts, company-wide parties and away days, plus regular team socials.
- Subsidised travel:Rail season ticket loan, free railcards, and a cycle to work scheme.
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