Numerai
Colaboratory
Infosec Skills
Explorium
Kaggle
DataSource.ai
edX
Driven Data
Split Fee
Unbench
Split Fee is a platform for UK recruitment agencies to collaborate on permanent placements.
Every agency has candidates they can't place and vacancies they can't fill. Another agency almost certainly has what you need โ but finding them, trusting them, and making the collaboration work has always been the hard part.
Split Fee solves this. Post your candidates and vacancies to the platform. Our matching algorithm finds opportunities across every agency on the network โ by skills, location, salary, and seniority. Candidate and client data stays anonymised until both sides agree to work together. When a placement is made, we handle the fee split and invoicing automatically.
No more posting in social media groups and hoping someone replies. No more sharing candidate details with strangers on trust alone. No more chasing invoices from agencies you barely know.
45% for you. 45% for them. 10% platform fee โ only when a placement is made.
Half of a placement fee is infinitely better than none of it.
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Split Fee's answer:
A next-generation serverless platform, built for AWS.
Split Fee's answer:
Split Fee is the first purpose-built platform for split fee recruitment in the UK. Instead of relying on LinkedIn groups, WhatsApp messages, and manual agreements, agencies upload their candidates and vacancies and the platform automatically matches them across agencies.
Candidate identities are revealed gradually; anonymised at first, then progressively disclosed as both sides accept, so agencies can collaborate without the risk of circumvention.
Split Fee's answer:
Most "split fee networks" are just directories or social groups where agencies post and hope someone responds. Split Fee is an actual matching engine. It scores candidate-vacancy pairs, handles the legal agreements (non-circumvention, self-billing), automates invoicing and fee splits, and manages the entire placement lifecycle from match to payment. Everything that normally requires trust, phone calls, and spreadsheets is handled by the platform.
Split Fee's answer:
UK recruitment agencies; from boutique firms with a handful of consultants to mid-sized agencies with specialist sector coverage. Any agency that has either strong candidates without the right vacancies, or client vacancies they can't fill from their own candidate pool. Split Fee turns those dormant assets into placements.
Split Fee's answer:
Abbie, our founder, knew that although split fee arrangements have existed in recruitment for decades, the process has always been manual: find a partner agency, negotiate terms, trust them with your candidate data, chase invoices. Most agencies avoid it because the overhead and risk outweigh the reward. Abbie built Split Fee to remove that friction entirely, with automated matching, progressive identity disclosure, built-in legal agreements, and automated billing, making split placements as straightforward as direct ones.
Based on our record, Numerai seems to be more popular. It has been mentiond 20 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Numerai? Though I'm not so sure - their coin seems to have lost a lot of dollar value since I last checked. https://numer.ai/. - Source: Hacker News / about 1 year ago
For example the Numerai hedge fund's data science tournament for crowdsourced stock market prediction is giving out their expensive hedge fund quality data to their users but it's transformed enough that the users don't actually know what the data is, yet the machine learning models are still working on it. To my knowledge it's not homomorphic encryption because that would be still too computational expensive, but... - Source: Hacker News / over 2 years ago
If you are interested in the machine learning part, you can try the Numerai tournament ( http://numer.ai ). They provide obfuscated high quality hedge fund data that participants can train their models on and send back only their predictions and then they combine the user's predictions into their market neutral meta model which they actively trade. So far their fund's returns looks promising in their category... - Source: Hacker News / over 3 years ago
This does not solve your problem, but you would be interested in https://numer.ai which is a "wisdom of the crowds" ML competition for stock market predictions. Source: about 4 years ago
Company: Numerai (https://numer.ai) Position: Web Developer Location: San Francisco (Remote/On-site with WFH days) Numerai is a new kind of hedge fund powered by thousands of competing data scientists from around the world, all working to predict the stock market. - Source: Hacker News / over 4 years ago
Colaboratory - Free Jupyter notebook environment in the cloud.
Unbench - Beyond recruitment, Unbench became a dynamic matchmaking platform, efficiently connecting companies with top specialists.
Infosec Skills - Infosec Skills is technical expertise and engineering development knowledge-building platform where engineers and technical experts can come together to share and learn about the latest security development techniques and strategies.
Explorium - Explorium is an External Data Platform that offers ML and AI-based datasets so data scientists can take part in data science competitors and marathons to win prizes.
Kaggle - Kaggle offers innovative business results and solutions to companies.
DataSource.ai - Community-funded data science tournaments
