Soccer Data Scientist - Europe in England
Soccer Data Scientist - Europe

Soccer Data Scientist - Europe in England

England Full-Time 50000 - 70000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and improve machine learning models for soccer data analytics.
  • Company: Join Swish Analytics, a cutting-edge sports analytics startup.
  • Benefits: Fully remote work, competitive salary, and opportunities for professional growth.
  • Why this job: Make an impact in the exciting world of sports betting with innovative data solutions.
  • Qualifications: Masters in Data Science or related field, with experience in sports analytics.
  • Other info: Collaborative team environment with a focus on technical excellence.

The predicted salary is between 50000 - 70000 £ per year.

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We are looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

Swish Analytics is hiring Soccer Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. We are hiring a Data Scientist to support our Sports Data Models.

Duties:
  • Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products.
  • Develop contextualized feature sets using specific domain knowledge in soccer.
  • Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.
  • Strive to constantly improve model performance using insights from rigorous offline and online experimentation.
  • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.
  • Adhere to software engineering best practices and contribute to shared code repositories.
  • Document modeling work and present to stakeholders and other technical and non-technical partners.
Requirements:
  • Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area.
  • Demonstrated experience developing models at production scale for soccer or sports betting.
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods.
  • Minimum of 3+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting.
  • Experience with relational SQL & Python.
  • Experience with source control tools such as GitHub and related CI/CD processes.
  • Experience working in AWS environments.
  • Proven track record of strong leadership skills.
  • Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions.
  • Excellent communication skills to both technical and non-technical audiences.

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.

Soccer Data Scientist - Europe in England employer: Swish Analytics

Swish Analytics is an exceptional employer for Soccer Data Scientists, offering a dynamic and innovative work culture that thrives on collaboration and creativity. With a strong focus on employee growth, we provide opportunities to develop cutting-edge predictive analytics products in a fully remote environment across Europe, allowing you to balance your professional aspirations with personal flexibility. Join us to be part of a passionate team dedicated to pushing the boundaries of sports data science while enjoying the benefits of a supportive and inclusive workplace.
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Contact Detail:

Swish Analytics Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Soccer Data Scientist - Europe in England

✨Tip Number 1

Network like a pro! Reach out to folks in the sports analytics field on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your data models and analyses, especially those related to soccer. This gives potential employers a taste of what you can bring to the table.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and being ready to discuss your past projects. We want to see how you think and solve problems, so be ready to dive deep!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.

We think you need these skills to ace Soccer Data Scientist - Europe in England

Machine Learning
Statistical Modelling
Probability Theory
Inferential Statistics
Bayesian Statistics
Markov Chain Monte Carlo methods
Data Analysis
Python
SQL
GitHub
CI/CD processes
AWS
Communication Skills
Problem-Solving Skills
Leadership Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Soccer Data Scientist role. Highlight your experience with machine learning and statistical models, especially in sports or soccer. We want to see how your skills align with our needs!

Show Your Passion: In your cover letter, let us know why you're passionate about soccer and data science. Share any personal projects or experiences that showcase your enthusiasm for predictive analytics in sports. We love seeing genuine interest!

Be Clear and Concise: When writing your application, keep it clear and concise. Use straightforward language to explain your technical skills and experiences. We appreciate a well-structured application that gets straight to the point!

Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!

How to prepare for a job interview at Swish Analytics

✨Know Your Soccer Stats

Make sure you brush up on your soccer statistics and data analysis skills. Understand the key metrics that drive performance in soccer and be ready to discuss how you've applied these in your previous work. This will show your passion for the sport and your technical expertise.

✨Showcase Your Model Development Experience

Prepare to talk about specific machine learning models you've developed, especially those related to sports betting or soccer. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your problem-solving skills and technical knowledge.

✨Communicate Clearly with All Audiences

Since you'll need to present your findings to both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Use examples from your past experiences to illustrate your points. This will highlight your communication skills, which are crucial for this role.

✨Familiarise Yourself with Their Tech Stack

Research Swish Analytics' tech stack, including SQL, Python, and AWS. If you have experience with GitHub and CI/CD processes, be prepared to discuss how you've used these tools in your projects. Showing that you're already familiar with their environment will give you an edge.

Soccer Data Scientist - Europe in England
Swish Analytics
Location: England

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