Data Scientist - United Kingdom
Data Scientist - United Kingdom

Data Scientist - United Kingdom

Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join our AI team to develop innovative machine learning models for sports data.
  • Company: Stats Perform, a leader in sports technology and data solutions.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Why this job: Make an impact in sports tech while solving complex data challenges.
  • Qualifications: Experience in data science or machine learning; passion for sports is a plus.
  • Other info: Dynamic team environment with mentorship and career advancement opportunities.

The predicted salary is between 36000 - 60000 £ per year.

Do you have a background in Data Science, Machine Learning, Computer Vision, Physics, Statistics or Probability Theory? Do you have a passion for sports? Do you live to find data driven solutions to complex problems? Come join our team at Stats Perform as a Data Scientist building predictive models with modern deep learning tools that will be utilized by the world’s leading technology companies, sports franchises and sports book operators.

Job Purpose:

The role is part of the AI Team with the purpose to bring new models & products to market at a fast pace. You will be part of a dynamic team which will work on solving complex problems by creating cutting edge models based on unique data sets, work with a team on launching the initial product, transition it into the product engineering function and move on to the next challenge.

WHAT’S YOUR NEW ROLE ABOUT

  • Research and modeling: Researching, developing, and implementing the most innovative machine learning techniques to Stats Perform’s wealth of sports data (both structured and unstructured).
  • Productizing artificial intelligence based solutions alongside engineers and product teams.
  • Providing technical guidance to product teams on the artificial intelligence (machine learning and computer vision) approaches appropriate for a task.
  • Patenting the innovative solutions.
  • Lifecycle and collaboration with our teams: Machine Learning lifecycle: data prep, training data generation, feature engineering, optimization, experimentation, reproducibility, deployment, and end-to-end workflow management.
  • Partners and stakeholders: identify data acquisition opportunities, create requirements, transform large volume data into AI ready high quality relevant datasets.
  • Accelerate the velocity from idea to interference into production.
  • Achieve quality ML data using a triad of people, process & technology.
  • Conduit between Product and Data Engineering to bring new models into production in a quick and efficient way.
  • Support, train and mentor team members on best ML implementation practices.

Enabling our products

ML and Deep Learning capabilities at vast scale by developing the necessary systems, tools, technologies and integrations as part of the ML Platform offering.

Our team members typically have:

  • Experience: At least 1 year of relevant industry experience in software engineering or machine learning and data science.
  • Hands on experience with building enterprise grade machine learning and data platforms.
  • Familiarity with common machine learning algorithms (random forest, XGBoost, etc.).
  • Preferred knowledge of advanced ML techniques (neural networks/deep learning, reinforcement learning, active learning, data augmentation and GANs etc.).
  • Experience with high-level programming languages such as Python and preferred knowledge of big data tools.
  • In-depth working knowledge of cloud infrastructure such as AWS or Google Cloud.
  • Proficiency in, at least, one modern deep learning engine such as Tensorflow, PyTorch etc. (preferred: knowledge of using GPUs).
  • Experience in integrating with internal and external complex systems that are able to scale and demonstrate security, reliability, scalability, and cost efficiency.
  • Experience in projects involving large scale multi-dimensional datastore, complex business infrastructure, and cross-functional teams, and track-record of successfully launched ML projects in production.
  • Passion for creating new technologies with high product impact within sport.

Education: Bachelor’s, MS or PhD in Computer Science, Mathematics, Computational Statistics, Machine Learning or related STEM fields.

Skills: Verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams, and both internal and external stakeholders. An open minded, structured thinker.

Data Scientist - United Kingdom employer: Stats Perform

At Stats Perform, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Data Scientist in the UK, you will have the opportunity to work with cutting-edge technology in the sports industry, while benefiting from continuous professional development and mentorship. Our commitment to employee growth, coupled with our dynamic team environment, makes us an ideal place for those passionate about data-driven solutions and sports.
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Contact Detail:

Stats Perform Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist - United Kingdom

✨Tip Number 1

Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even local sports events. You never know who might have a lead on your dream job!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and data science. Share it on platforms like GitHub or your personal website to grab the attention of potential employers.

✨Tip Number 3

Prepare for interviews by practising common data science questions and case studies. Mock interviews with friends or mentors can help you feel more confident and ready to tackle any question thrown your way.

✨Tip Number 4

Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in the sports data world. Your next big opportunity could be just a click away!

Some tips for your application 🫡

Show Your Passion: Let us see your enthusiasm for data science and sports! Mention any relevant projects or experiences that highlight your love for solving complex problems with data. This will help us connect with you on a personal level.

Tailor Your CV: Make sure your CV is tailored to the role. Highlight your experience with machine learning, deep learning, and any relevant tools you've used. We want to see how your skills align with what we're looking for!

Craft a Compelling Cover Letter: Your cover letter is your chance to tell your story. Explain why you're excited about this role at Stats Perform and how your background makes you a great fit. Keep it concise but impactful!

Apply Through Our Website: We encourage you to apply directly 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!

How to prepare for a job interview at Stats Perform

✨Know Your Data Science Fundamentals

Brush up on your knowledge of machine learning algorithms and techniques, especially those mentioned in the job description like random forests and deep learning. Be ready to discuss how you've applied these in past projects, as this will show your practical experience.

✨Show Your Passion for Sports

Since the role is with a sports-focused company, make sure to express your enthusiasm for sports. Share any relevant experiences where you've combined your love for sports with data science, whether it's through personal projects or professional work.

✨Prepare for Technical Questions

Expect technical questions that may involve coding challenges or problem-solving scenarios. Practice coding in Python and be familiar with tools like TensorFlow or PyTorch. You might be asked to explain your thought process while solving a problem, so articulate clearly.

✨Demonstrate Collaboration Skills

The role involves working closely with product teams and engineers. Prepare examples of how you've successfully collaborated in the past, highlighting your communication skills and ability to bridge the gap between technical and non-technical stakeholders.

Data Scientist - United Kingdom
Stats Perform
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