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Machine Learning Developer - Quant Strategies

Newton Colmore Consulting Ltd
Posted 12 hours ago, valid for a day
Location

London, Greater London EC1R 0WX

Salary

£50,000 - £60,000 per annum

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Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • An innovative investor is seeking a Machine Learning Developer to focus on quantitative strategies and research.
  • Candidates should have a degree in Mathematics, Computer Science, or Physics, along with strong knowledge of Python or C++ and hands-on development experience in a scientific field or quant strategy.
  • The role involves building statistical models across various applications, liaising with business partners, and delivering robust solutions.
  • The company offers a highly competitive salary along with excellent career progression, training, and relocation packages.
  • It is anticipated that candidates will have several years of relevant experience to be considered for this exciting opportunity.

Machine Learning Developer - Quant Strategies

An exciting position has become available with an innovative investor who is looking for a Machine Learning Developer to focus on quantitative strategies and research.

This exciting new role will give the Machine Learning Developer an opportunity to work alongside some of the brightest minds in the industry as well as on some of the most exciting technologies in the sector.

In terms of day to day activities you will be building brand-new statistical models across a number of different applications/sectors including equities and commodities. You will be liaising with partners from across the business with the sole aim of delivering robust solutions to their requirements and outperforming the competition.

This role will provide you with a forward-thinking work environment whilst also giving you the opportunity to make a real-world difference. It is anticipated that you will become the machine learning authority and will regularly attend events and delivery presentations.

To be considered for this exciting role you will need to have a degree in Mathematics, Computer Science or Physics as well as strong knowledge of python or C++. This will be coupled with hands-on development experience within a highly scientific field or quant strat.

In exchange for your skills and expertise, the company offer a highly competitive package as well as providing excellent career progression and training. The company also offer relocation packages to make a move as easy as possible for you. Due to the nature of the business you will always have something new on the horizon as well time dedicated to personal projects and ideas.

For more information, please call Matt Lowdon of Newton Colmore Consulting on or make an application and one of our team will be in touch.

Newton Colmore Consulting is a highly specialist recruitment consultancy operating within the medical devices, machine learning and scientific technology sectors, across Europe. We partner with companies, ranging from early stage start-ups through to multinationals, helping them secure highly sought after skill sets.

Key words: Data Scientist, Algorithm Developer, Equity Research, Investments, Quantitative Research, Bayesian Statistics, Mathematics, Computer Science, Analytical Algorithms, Python. C++, Monte Carlo.

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In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.