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- Tasks: Join us as a Data Scientist to enhance football match predictions and develop practical modeling solutions.
- Company: Be part of a dynamic team focused on betting and prediction innovations.
- Benefits: Enjoy flexible working hours and the option to work from home one day a week.
- Why this job: Dive into a role that combines your passion for football with data science, making a real impact.
- Qualifications: Strong problem-solving skills, experience in SQL, Python, and statistical analysis required.
- Other info: Senior candidates can lead projects and shape research direction.
The predicted salary is between 28800 - 48000 £ per year.
Our client is searching for a Data Scientist to work on the betting and prediction side of their business, helping them to improve their ability to predict match outcomes. This role involves researching ways in which the modelling approaches they use to predict football matches can be improved, and then turning those insights into practical modelling solutions that they can deploy to production.
Our client offers a degree of flexibility regarding daily working hours, and you will have the opportunity to work from home one day per week. However, please note that fully remote candidates are not being considered.
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Strong problem solving skills, with an ability to proactively identify challenges and propose solutions
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Interest in football and betting/prediction problems
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An ability to make pragmatic and sensible choices about what data analysis and modelling approaches to use – you can judge when it’s right to obsess about the details, and when it’s right to ship an MVP as fast as possible.
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A flair for communicating statistical analyses to both technical and non-technical audiences
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Experience with statistical analysis and predictive modelling – you don’t need to be an expert in any one area, but you need to know what techniques and tools are available, and understand the trade-offs of using different approaches
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Experience with SQL and relational databases – you can quickly understand a new dataset, perform exploratory analysis, identify data quality issues, and take pragmatic decisions about how to handle imperfect data
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Some programming experience, preferably with Python.
For senior candidates:
More experienced candidates will have the opportunity to take on more responsibility, leading projects and helping set the direction of the research.
They are looking for candidates who can think strategically and make pragmatic decisions about where they should focus their efforts, and what technical approaches they should use to get the modelling ideas onto production. In addition to the requirements above, this means you also have:
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3+ years of practical data science experience
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Project management skills, including an ability to make sensible value judgements about where the team should spend time
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An extensive knowledge of statistical methods and machine learning techniques
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Strong programming skills, ideally with Python
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Experience working with other data scientists on a collaborative codebase
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Experience of deploying models to production, ideally in AWS or another cloud environment
Data Scientist employer: BettingJobs
Contact Detail:
BettingJobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your problem-solving skills during the interview. Prepare examples of how you've proactively identified challenges in past projects and the solutions you proposed. This will demonstrate your ability to think critically and strategically, which is crucial for this role.
✨Tip Number 2
Since the role involves predicting football match outcomes, brush up on your knowledge of football and betting strategies. Being able to discuss relevant trends or recent matches can show your genuine interest in the field and help you connect with the interviewers.
✨Tip Number 3
Familiarize yourself with the latest statistical analysis and predictive modeling techniques. Be ready to discuss the trade-offs of different approaches and how you would apply them to real-world scenarios, especially in relation to football data.
✨Tip Number 4
If you have experience with deploying models to production, particularly in cloud environments like AWS, be sure to highlight this. Discuss any collaborative projects you've worked on with other data scientists, as teamwork is essential in this role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the specific requirements for the Data Scientist position. Highlight your relevant experience in predictive modeling, statistical analysis, and any interest you have in football and betting.
Tailor Your CV: Customize your CV to emphasize your problem-solving skills, programming experience (especially with Python), and familiarity with SQL and relational databases. Include specific examples of past projects where you improved data analysis or modeling approaches.
Craft a Compelling Cover Letter: Write a cover letter that not only showcases your technical skills but also your passion for football and betting. Discuss how your experience aligns with the company's goals and how you can contribute to improving their prediction models.
Highlight Collaboration Experience: If you have experience working in teams or collaborating with other data scientists, make sure to mention this. Emphasize your ability to communicate complex statistical analyses to both technical and non-technical audiences, as this is crucial for the role.
How to prepare for a job interview at BettingJobs
✨Show Your Passion for Football and Data
Make sure to express your genuine interest in football and how it relates to data science. Share any personal projects or experiences where you've combined these two passions, as this will resonate well with the interviewers.
✨Demonstrate Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you approached solving them. Highlight your ability to identify issues proactively and propose practical solutions, especially in the context of predictive modeling.
✨Communicate Clearly
Practice explaining complex statistical analyses in simple terms. Be ready to showcase your ability to communicate effectively with both technical and non-technical audiences, as this is crucial for the role.
✨Familiarize Yourself with SQL and Python
Brush up on your SQL skills and be prepared to discuss your experience with relational databases. Additionally, highlight your programming experience in Python, as this will be a key part of your role in deploying models to production.