Hybrid Sports Quant Analyst: Build Predictive Models

Mustard Systems Ltd.

United Kingdom

On-site

GBP 45,000 - 65,000

Full time

14 days+
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Benefits offered by this job

Hybrid work
Health insurance
Life assurance
Sabbatical leave
33 days annual leave
Pension plan
Bonus potential

Job summary

Mustard Systems in the United Kingdom is seeking talented individuals for its Quant team to develop predictive models used in cricket and trading. You will research recent advances in modelling, design and build your own models, and work closely with expert traders and developers to extract signals from noisy data.

You will join a close-knit team of mathematicians with high responsibility early on, supported by a hybrid working pattern (office Mon/Tue/Thu; WFH Wed/Fri) and comprehensive

Qualifications

  • A 1st class degree from a top university or a 2:1 from Oxbridge.
  • Degree-level study in statistics and probability theory.
  • Intellectual curiosity, creativity and confidence to try new approaches.
  • Excellent problem solving and communication skills.
  • An interest in sports or competitive games. No cricket knowledge required!

Responsibilities

  • To research recent advances in modelling to better extract signals from noisy data
  • To join a close-knit, collaborative team of mathematicians and enjoy a high level of responsibility from an early stage
  • To design and build your own models using your own ideas
  • To work closely with expert traders and developers to improve your models
  • Learn to build the best models from experienced quants

Education

First-class degree in a quantitative field

Job description

Mustard Systems in the United Kingdom is seeking talented individuals for its Quant team to develop predictive models used in cricket and trading. You will research recent advances in modelling, design and build your own models, and work closely with expert traders and developers to extract signals from noisy data.

You will join a close-knit team of mathematicians with high responsibility early on, supported by a hybrid working pattern (office Mon/Tue/Thu; WFH Wed/Fri) and comprehensive

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