Engineering Internships For Algorithmic Trading & Computer Vision

Job description

We are looking for computer science/mathematics/engineering undergraduates highly motivated intern to work on various engineering changes and to solve problems with high-dimensional state and/or action spaces.

In terms of skills you don’t need them all, but the more of the below you can tick the better:-

Excellent academic record in a numerate subject such as Computer Science, Maths, Engineering
Programming experience, e.g. projects done in spare time or at university (the bigger the better)
C++, C# or Python languages (if you are interested in platform development)
HTML / CSS / JavaScript / AngularJS / Rails etc. (if you are interested in web app development)
Knowledge or experience with algorithmic trading/sports
Git & Linux

The candidate should be comfortable implementing the prototypes of the developed algorithms in Python and work with our infrastructure.
The candidate should expect to receive a First Class Degree or High Upper Second Class Degree with demonstrable coding experience.
Intern Projects Include:
Computer Vision
Use internal platform id for a football match of particular league in a particular week
Use database query or python utility to get all ids for that particular week for which we have chance entries.
Log onto instatscout and download all matches of that week for which we have chances
Run in house utility to verify the timing of the chances.
Help transfer all games to an ftp server/amazon account

Recommendation Systems & Algorithmic Trading
Recommend trading ideas based on Game States
Build Trading Indicators
Game suggestions using past logs
Help build front ends for automated trading agent training (using reinforcement learning)

Candidates with in-depth sports knowledge, experience of modelling sporting events or experience in financial quantitative analysis are particularly encouraged to apply. Equally we are seeking candidates eager to take their first steps on a career path, or looking to move from an academic to a commercial environment.
THE COMPANY
Stratagem was founded in 2012 and represents the culmination of knowledge and expertise derived from a wealth of experience in both the financial markets and the sports betting industry. In 2015 the company was named one of the 20 Most Promising Sports Technology Solutions Providers by CIO Review.

HOW TO APPLY
To apply for the role please email your CV and a covering letter (with the job title ‘Engineering Internship’ in the subject of the email)
Tell us how working for Stratagem will help achieve our goals and yours. Shortlisted candidates will be invited for interview and will be required to demonstrate proficiency by completing an in-house technical exercise.
We respectfully note that we will not be retaining recruitment consultant for this position and will simply not reply to unsolicited applications or enquiries from such parties.

Desired profile

YOUR PROFILE
We are seeking talented and motivated candidates with a background or experience in computational statistical modelling and / or machine learning. You will join us to work with a group of high-achieving quantitative researchers who love sport and who love solving difficult problems. You will be able to demonstrate your abilities through tangible work and discrete projects, with constant feedback from real world events and you should be confident enough to contribute ideas and challenge assumptions from your first day.
You will have achieved an undergraduate degree a scientific subject with considerable statistical or data science content. This will be backed up by an excellent coding ability.
While applicants are likely to have specialist skills in specific areas, we want team players who love what they do and are willing to push themselves beyond their comfort zone. Our existing technology utilises Python, C++ and MongoDB, and where possible we use open source technologies. However, we strongly believe in using the right tool for the job, so are always open to new approaches that present the opportunity to improve business value.