Quantitative Analyst

Quantitative Analyst

Full-Time 28800 - 48000 Β£ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and manage sports prediction models using modern tools.
  • Company: Join a leading sports betting software provider in London.
  • Benefits: Enjoy flexible working hours and a relaxed team environment.
  • Why this job: Work with cutting-edge technology and collaborate with industry experts.
  • Qualifications: 1st class maths degree or 2:1 from Oxbridge; strong stats knowledge required.
  • Other info: Postgraduate qualifications in statistics preferred; no sponsorship available.

The predicted salary is between 28800 - 48000 Β£ per year.

Quantitative Analyst – Sports betting – London

*Please note this role cannot sponsor. Please do not apply if you are seeking sponsorship*

Job Summary

Quantitative Analyst is required for a successful startup delivering innovative solutions to the sports betting industry. They capitalize on advanced statistical models and machine learning to interpret the complexities of sports, providing deep analytical insights.

As Quantitative Analyst you will need:

  • 4 years’ experience as a quantitative analyst or data scientist within sports betting industry.
  • A mathematics-based degree from a top university
  • Expertise in Bayesian statistics, MCMC, and GLMs
  • Knowledge of sports models literature
  • Proficient in SQL and Python/R
  • Demonstrated experience building and delivering ML and statistical models

Responsibilities and Duties

  • You will be working autonomously on the modelling efforts as you wouldn\’t be involved in working with the existing models.
  • Analysing, cleaning, and processing raw data
  • Developing, improving, and maintaining ML and statistical models for risk management
  • Analyse data and perform inferences to understand betting markets and customers behaviour

The Opportunity

  • Opportunities to progress your quantitative developer career
  • Working in GLMs, BMMs, Kalman filters, MCMC and the TrueSkill Ranking system

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Quantitative Analyst employer: Venture Up

As a leading provider of sports betting brokerage software, this company offers an exceptional work environment in London, characterised by flexible working hours and a relaxed atmosphere. Employees benefit from opportunities for professional growth, collaborating with industry experts while utilising cutting-edge tools to innovate and enhance predictive models in a dynamic field. Joining this team means being part of a culture that values intellectual curiosity and creativity, making it an ideal place for aspiring quantitative analysts to thrive.
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Contact Detail:

Venture Up Recruiting Team

StudySmarter Expert Advice 🀫

We think this is how you could land Quantitative Analyst

✨Tip Number 1

Familiarise yourself with the specific tools mentioned in the job description, like Jupyter, PyTorch, and Spark. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.

✨Tip Number 2

Engage with the sports betting community online. Join forums or social media groups where discussions about statistical models and predictions take place. This will not only enhance your knowledge but also show your genuine interest in the field.

✨Tip Number 3

Consider creating a portfolio of your own predictive models or analyses related to sports. This practical demonstration of your skills can be a great conversation starter during interviews and showcases your initiative.

✨Tip Number 4

Network with professionals in the quantitative analysis and sports betting sectors. Attend relevant meetups or webinars to connect with industry experts, which could lead to valuable insights and potential referrals for the role.

We think you need these skills to ace Quantitative Analyst

Statistical Analysis
Probability Theory
Regression Analysis
Model Fitting
Bayesian Updating
Data Modelling
Programming Skills in Python
Experience with Jupyter Notebooks
Familiarity with PyTorch
Knowledge of Spark
Intellectual Curiosity
Creativity in Problem Solving
Interest in Sports and Competitive Games
Collaboration with Traders and Developers
Ability to Work with Large Datasets

Some tips for your application 🫑

Tailor Your CV: Make sure your CV highlights your mathematics-based degree and any relevant coursework or projects related to statistical prediction and probability theory. Emphasise your experience with tools like Jupyter, PyTorch, and Spark if applicable.

Craft a Strong Cover Letter: In your cover letter, express your intellectual curiosity and creativity. Mention specific examples of how you've applied statistical methods or built models in the past, and relate this to your interest in sports or competitive games.

Showcase Relevant Skills: Clearly outline your understanding of regression, model fitting, and Bayesian updating in your application. If you have any postgraduate qualifications in statistics, be sure to highlight these as they are preferred for the role.

Proofread Your Application: Before submitting, carefully proofread your application for any errors or inconsistencies. A well-presented application reflects your attention to detail, which is crucial for a Quantitative Analyst role.

How to prepare for a job interview at Venture Up

✨Showcase Your Mathematical Skills

Make sure to highlight your strong mathematical background during the interview. Be prepared to discuss specific concepts such as regression, model fitting, and probability theory, as these are crucial for the role.

✨Demonstrate Your Passion for Sports

Since the role is in sports betting, express your interest in sports or competitive games. Share any relevant experiences or insights that showcase your enthusiasm and understanding of the industry.

✨Prepare for Technical Questions

Expect technical questions related to statistical prediction and algorithms. Brush up on your knowledge of Bayesian updating and be ready to discuss how you would apply these concepts to real-world scenarios.

✨Exhibit Intellectual Curiosity

The company values creativity and a willingness to explore new approaches. Be prepared to discuss past projects where you demonstrated innovative thinking or problem-solving skills, especially in data analysis or model development.

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