Kingston University  /Instinet
graduate job
Expires2 days

Machine Learning Scientist

Job description

This is a unique and exciting opportunity, supported by Kingston University academics and based at Instinet, a leading global broker of equities, in London. This KTP project will develop and deploy innovative machine learning techniques for trading execution performance and monitoring.

You will have primary responsibility for the application of these techniques, to deploy machine-learned products to improve the execution performance of equity trading, and machine-learned tools to monitor this performance. You will also have responsibility for authoring reports and academic publications that describe aspects of your work, and the potential impact for Instinet and its clients.

You will be working alongside another KTP Associate, employed as a Systems Architect.

This position is a 32-month fixed-term contract.

The university partner
This KTP will be led academically by Prof James Orwell and supervised by Dr Gordon Hunter from the School of Computer Science and Mathematics school within the Faculty of SEC.

What we are looking for

The ideal candidate will have a solid understanding of:

  • Theoretical principles of machine learning
  • Linear algebra
  • Probability and statistics
  • Capability to use system output information to diagnose and fix deficiencies in implementation,
  • Incorrect assumptions about data, etc and experience in testing and correcting computer programs designed for specialised operating conditions

Qualifications

You will have a BSc (minimum of 2:1) in a subject with significant mathematical content plus MSc in mathematics, computer science or a closely related subject. And possibly a PhD in similar subjects.

Accepted degree subjects

  • mathematics
  • computer sciences and IT

Additional job details

Number of vacancies
One
Location
South East England
Salary
£50,000 to £70,000

Salary depending on qualifications and experience plus training package of up to £2,000

Contract, dates and working times
Fixed term

Full-time

How to apply

Interviews: week commencing 8 July or 15 July.

If you have any questions please email.

Click Apply to start your application now. This job will be available on Prospects until 28 June 2019

Don't forget to mention Prospects to employers when you contact them.

Closing date:  28 June 2019

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Expires2 days

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