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Auquan
Auquan is a high growth data science company operating in the fintech space and based in London, UK. A graduate of Techstars 2018, Auquan closed its seed round in early 2019 with a plan to become the data science platform for the finance industry. Currently, they serve London’s institutional investors with data science and machine learning solutions to their investment problems. Auquan does this by turbocharging their in-house data science team with solutions from their global community of over 13,000 data scientists who come from a wide range of backgrounds, including both the professional world (e.g. google and uber) and academia (MIT and Oxford). Solutions are sourced via their competition platform and then combined and developed in-house into a deployable solution for the client. Clients have included: Optiver, & Global Asset Managers with $300bn & 500bn assets under management.
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- Member Since: 14/12/19
Profile | Name | Role | Email Address | Slack | Skills | ||
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Chandini Jain | Founder/CEO | [email protected] | https://www.linkedin.com/in/chandinijain/ | Slack to be added | Quantitative Finance, Data Science, Statistics | ||
Shub Jain | Founder/CTO | [email protected] | https://www.linkedin.com/in/shubj/ | Slack to be added | Dancing | ||
David Ardagh | Marketing & Community | [email protected] | https://www.linkedin.com/in/davidardagh/ | Slack to be added | Community building, Marketing |
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Auquan provides data science solutions to Investment Managers to add machine learning to their investment decisions, without requiring any internal data science capabilities. Auquan takes clients investment problems and returns investment solutions - in the language of finance. In between, Auquan will frame their question into a data science problem, prepare their data, remove financial domain knowledge, anonymise the data, run a competition for our 13000 data scientists to get community-generated answers, test, verify and ensemble the solutions and prepare a single implementable solution that matches the client's needs. Solutions are accompanied by detailed model explanations, results analysis and implementation support, all for a fraction of the price of an in-house team.