At a Glance
- Tasks: Join our trading team to analyse sports data and develop predictive models for automated trading.
- Company: Pythia Sports is a dynamic tech company specialising in predictive sports modelling and data collection.
- Benefits: Enjoy hybrid work, private health insurance, 36 days holiday, and exciting development opportunities.
- Other info: Ideal for those passionate about sports, gambling, and trading.
- Why this job: Be part of a creative team in a relaxed atmosphere with monthly social events and innovative projects.
- Qualifications: Must be graduating by summer 2025 with a numerate degree and strong Python skills.
The predicted salary is between 28800 - 48000 £ per year.
Pythia Sports are looking for creative thinking and experienced graduates or final year students 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 2025 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:
- Recently graduated or graduating by summer 2025 with a good numerate degree.
- Practical experience with statistics and machine learning.
- Strong Python programming skills, with knowledge of Pandas, Numpy and Scipy.
- Experience with SQL.
- A track record of using data to solve complex problems.
- Knowledge and interest in sports, gambling and trading will be helpful.
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! 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.
Trading Data Scientist Graduate in London employer: Pythia Sports
Pythia Sports is an exceptional employer that fosters a dynamic and innovative work environment in the heart of London Victoria. With a strong emphasis on employee well-being, we offer comprehensive benefits including private health insurance, enhanced parental leave, and ample career development opportunities. Our hybrid work model promotes a balanced lifestyle, while our collaborative culture encourages creativity and teamwork, making it an exciting place for talented individuals to thrive and make a meaningful impact in the gaming industry.
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We think this is how you could land Trading Data Scientist Graduate in London
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We think you need these skills to ace Trading Data Scientist Graduate in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Prepare for Case Studies
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