At a Glance
- Tasks: Develop and improve machine learning models for cutting-edge sports betting products.
- Company: Join Swish Analytics, a dynamic startup revolutionising sports analytics.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on innovation and technical excellence.
- Why this job: Make a real impact in the exciting world of sports data science.
- Qualifications: Masters in Data Science or related field with experience in sports betting models.
The predicted salary is between 36000 - 60000 £ 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.
Soccer Data Scientist - Europe in London employer: Swish Analytics
Swish Analytics is an exceptional employer for those passionate about sports analytics and customer success. With a fully remote work environment, employees enjoy the flexibility of working from anywhere within the CET time zone while being part of a dynamic team that values creativity and technical excellence. The company fosters a collaborative culture, offering ample opportunities for professional growth and development, making it an ideal place for individuals eager to make a meaningful impact in the sports betting industry.
StudySmarter Expert Advice🤫
We think this is how you could land Soccer Data Scientist - Europe in London
✨Tip Number 1
Network like a pro! Reach out to folks in the sports analytics field, especially those at Swish Analytics. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning models and data analysis projects, particularly those related to soccer. This will help us see your passion and expertise in action.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We love candidates who can communicate complex ideas clearly, so practice explaining your work to non-technical friends!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you're genuinely interested in being part of the Swish team.
We think you need these skills to ace Soccer Data Scientist - Europe in London
Some tips for your application 🫡
Show Your Passion for Soccer:When you're writing your application, let your love for soccer shine through! We want to see how your passion aligns with our mission at Swish Analytics. Share any relevant experiences or projects that highlight your enthusiasm for the sport and data.
Highlight Your Technical Skills:Make sure to showcase your technical expertise in data science, especially in machine learning and statistical models. We’re looking for someone who can hit the ground running, so don’t hold back on detailing your experience with Python, SQL, and any other relevant tools.
Tailor Your Application:Take a moment to customise your application for the Soccer Data Scientist role. Mention specific projects or achievements that relate directly to sports betting or soccer analytics. This shows us you’ve done your homework and are genuinely interested in this position.
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 gives you a chance to explore more about what we do at Swish Analytics!
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 techniques. Familiarise yourself with the latest trends in sports analytics, especially those related to soccer. Being able to discuss specific models or algorithms you've worked on will show your passion and expertise.
✨Showcase Your Technical Skills
Be prepared to demonstrate your proficiency in Python, SQL, and any machine learning frameworks you've used. You might be asked to solve a problem on the spot, so practice coding challenges beforehand. Highlight any experience with AWS or GitHub as well, as these are crucial for the role.
✨Communicate Clearly
Since you'll be working with both technical and non-technical teams, practice explaining complex concepts in simple terms. Prepare examples of how you've successfully communicated your findings in the past. This will help you stand out as a candidate who can bridge the gap between data science and business needs.
✨Prepare Questions About Their Products
Research Swish Analytics' current products and think about how your skills can contribute to their development. Prepare insightful questions that show your interest in their work and how you can add value. This not only demonstrates your enthusiasm but also your proactive approach to understanding their business.
