Trading Data Science Grad

pythiasportsยท Trading
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About this role

Pythia Sports are looking for creative thinking and experienced graduate or final year student to join their in-house exchange trading team.

The purpose of the role is to conduct statistical analysis of sports events, developing predictive models which can be used to create and refine automated trading strategies.

Successful candidates should be innovative and self-driven, with high levels of integrity. They will be working closely with local and remote teams and therefore need to be highly communicative, but also work well independently. They must be well organised and have the ability to handle projects with many moving parts.

Applicants are required to have graduated by 2026 with a good numerate degree

Hybrid role: Minimum 2 days working in the London office


Main responsibilities:

  • Develop a deep understanding of the data, its limitations and meaning, including the investigation of data validity
  • Build and analyse data-driven predictive trading models
  • Select or build model validation metrics to evaluate model performance
  • Develop automated trading strategies - backtesting, paper and production trading


Key Skills / Qualifications:

  • Fresh grad or graduating by summer 2026 with a solid computer science, data science, math, or stats degree.
  • Hands-on experience with stats and machine learning.
  • Good with Python and Message Queues.
  • Experience in using SQL database.
  • Familiar with both Windows and Linux.
  • Proven track record of using data to solve tricky problems.
  • It's a big plus if you love sports, gambling, or trading.


Company Overview

Pythia Sports is a fast growing technology company with a focus on predictive sports modelling and data collection. We focus on being the best at what we do and recognise that our success comes from having the best employees and keeping them happy. We pride ourselves on hiring talented, creative and free thinkers.

Here you will find a relaxed atmosphere, monthly social events and amazing people!ย 

We also offer private health and dental insurance, cycle to work scheme, enhanced paternity and maternity leave, enhanced sick pay, 36 days holiday total allowance and exciting development opportunities.

Pythia Sports employees are expected to embrace the company philosophy of integrity combined with innovation and cutting edge technology.

Frequently Asked Questions

Is the salary disclosed for the Trading Data Science Grad position at pythiasports?
The salary for this Trading Data Science Grad role at pythiasports is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Trading Data Science Grad position at pythiasports located?
This Trading Data Science Grad role at pythiasports is based in Hybrid, LONDON, Greater London, United Kingdom. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Trading Data Science Grad role at pythiasports full-time or part-time?
This is listed as a Full Time position. It is posted as a Trading Data Science Grad role in the Trading department at pythiasports.
Which team or department does the Trading Data Science Grad at pythiasports belong to?
This Trading Data Science Grad position is part of the Trading department at pythiasports. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Trading Data Science Grad position at pythiasports?
Click the "Apply Now" button on this page. You will be redirected to pythiasports's official application portal hosted on bamboohr where you can submit your application directly.
When was the Trading Data Science Grad job at pythiasports posted?
This Trading Data Science Grad position at pythiasports was posted on Jun 8, 2026. Apply as soon as possible โ€” early applications are often reviewed first.
Trading Data Science Grad
pythiasports
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You'll be redirected to pythiasports's official application page on bamboohr.