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- Tasks: Join a prediction team to enhance sports analytics through data analysis and innovative modeling.
- Company: Be part of a dynamic team focused on sports analytics and predictive modeling.
- Benefits: Enjoy generous leave, health perks, gym subsidies, and learning budgets.
- Why this job: Work collaboratively while exploring your ideas in a fast-paced sports environment.
- Qualifications: 3+ years in predictive modeling; strong Python skills; experience with sports or gaming data.
- Other info: 4 days onsite, 1 day work from home for a balanced work-life.
The predicted salary is between 36000 - 60000 £ per year.
Quantitative Analyst
4 days onsite, 1 day wfh
About the Role
My client is seeking a Quantitative Analyst to join their prediction team. You will use extensive datasets to enhance predictive models, explore new methodologies, and develop solutions. This role involves a blend of in-depth analysis and innovative modelling to tackle unique challenges in sports analytics. You will be joining a collaborative team of data scientists and sports analysts, as well as having the freedom to explore and develop individual ideas.
Requirements
- 3+ years of experience in predictive modelling, machine learning, and probability theory, preferably in the sports or gaming/betting industries.
- Familiarity with techniques such as Monte Carlo simulation, Bayesian modelling, mixed effects models, Kalman filters, GLMs, and time series forecasting.
- Strong programming skills, particularly in Python.
- Experience in exploring new datasets, identifying data quality issues, and handling imperfect data effectively.
Preferred Qualifications
- Understanding of expected value and utility principles.
- Practical problem-solving approach, balancing detail with quick delivery of MVPs.
- Ability to independently deliver projects and make informed decisions..
What you'll get
- Generous annual leave (including bank holidays)
- Competitive pension contributions
- Health and well-being benefits
- Subsidised gym membership and meals
- Learning and development budgets
- Regular sports activities with colleagues
Interested? Apply to this role or send your CV directly to to be considered.
Quantitative Analyst - Football employer: Harrington Starr
Contact Detail:
Harrington Starr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst - Football
✨Tip Number 1
Familiarize yourself with the specific predictive modeling techniques mentioned in the job description, such as Monte Carlo simulation and Bayesian modeling. Being able to discuss these methodologies in detail during your interview will demonstrate your expertise and passion for the role.
✨Tip Number 2
Showcase your programming skills in Python by working on relevant projects or contributing to open-source initiatives. Having tangible examples of your coding abilities can set you apart from other candidates and highlight your practical experience.
✨Tip Number 3
Stay updated on the latest trends and developments in sports analytics. Being knowledgeable about current events and innovations in the field will allow you to engage in meaningful conversations during interviews and show your commitment to continuous learning.
✨Tip Number 4
Prepare to discuss how you've handled imperfect data in past projects. Sharing specific examples of your problem-solving approach will illustrate your ability to navigate challenges and deliver results, which is crucial for this role.
We think you need these skills to ace Quantitative Analyst - Football
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your 3+ years of experience in predictive modeling, machine learning, and probability theory. Tailor your CV to showcase any relevant projects or roles you've held in the sports or gaming industries.
Showcase Technical Skills: Clearly outline your programming skills, especially in Python. Include specific examples of how you've used techniques like Monte Carlo simulation, Bayesian modeling, or time series forecasting in your previous work.
Demonstrate Problem-Solving Abilities: In your cover letter, provide examples of how you've approached complex problems in the past. Highlight your practical problem-solving approach and your ability to deliver MVPs quickly while maintaining attention to detail.
Express Your Passion for Sports Analytics: Convey your enthusiasm for sports analytics in your application. Discuss any personal projects or interests related to sports data analysis that demonstrate your commitment to the field.
How to prepare for a job interview at Harrington Starr
✨Showcase Your Technical Skills
Be prepared to discuss your experience with predictive modeling and machine learning techniques. Highlight specific projects where you've used methods like Monte Carlo simulation or Bayesian modeling, and be ready to explain your approach and the outcomes.
✨Demonstrate Problem-Solving Abilities
Prepare examples that showcase your practical problem-solving skills. Discuss how you've balanced detail with quick delivery in past projects, and be ready to share how you approached challenges in sports analytics.
✨Familiarize Yourself with Sports Analytics
Since this role is focused on football, brush up on current trends and methodologies in sports analytics. Being able to discuss recent developments or case studies in the field will show your passion and understanding of the industry.
✨Ask Insightful Questions
Prepare thoughtful questions about the team's current projects and methodologies. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your career goals and values.
