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- Tasks: Develop innovative models and data-driven solutions for enhancing the Sportsbook experience.
- Company: Join DraftKings, a leading tech company shaping the future of sports and AI.
- Benefits: Competitive salary, gaming license support, and opportunities for professional growth.
- Why this job: Be part of a dynamic team transforming sports with cutting-edge technology and AI.
- Qualifications: Degree in a related field and proficiency in Python; passion for American football is a plus.
- Other info: Collaborative environment with opportunities to mentor junior data scientists.
The predicted salary is between 36000 - 60000 £ per year.
At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together.
Our Sports Modeling team comprises sports modeling experts and data science technologists, coming together to develop innovative products that deliver incremental value across our Sportsbook platform for American Football. As a Senior Data Scientist on the Sports Modeling team, you will develop models and data-driven solutions that enhance the Sportsbook experience for our users. In this role, you will work on implementing advanced sports models, refining data assets, and ensuring seamless integration into applications.
What You'll Do
- Create statistical and machine learning models and integrate them into data science applications.
- Collect and engineer sports data assets to assist in model development.
- Implement the sports models and pricing engines in Python.
- Create automatic tests to ensure model and pricing engine accuracy.
- Collaborate closely with Trading, Product, Engineering, and QA teams to move projects from ideation to deployment.
- Test data flows and model integration in a larger business context.
- Coach and support more junior data scientists within the team.
What You'll Bring
- A college degree in Statistics, Data Science, Mathematics, Computer Science, Engineering, or another related field.
- Proficiency in Python, object-oriented programming concepts, and version control.
- Familiarity with unit testing, integration testing, and CI/CD pipelines to support code quality and reliability.
- Familiarity with containerization tools like Docker and orchestration platforms such as Kubernetes.
- Experience with the machine learning lifecycle (experimentation, reproducibility, deployment, monitoring, retraining).
- Solid grasp of data science principles and statistical modeling techniques, preferably with experience building statistical or machine learning models for sports.
- Demonstrated passion for sports (American football preferred) and a strong understanding of relevant leagues and their dynamics.
- Self-motivation and eagerness to expand knowledge and understanding of Sportsbook products and related technologies.
We’re a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don’t worry, we’ll guide you through the process if this is relevant to your role.
Senior Data Science Engineer, American Football in London employer: DraftKings
Contact Detail:
DraftKings Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Science Engineer, American Football in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at DraftKings. 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 data science projects, especially any related to sports. This is your chance to demonstrate how you can enhance the Sportsbook experience.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and machine learning concepts. Be ready to discuss how you've tackled real-world problems with your models—this is what will impress the hiring team!
✨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, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Senior Data Science Engineer, American Football in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Science Engineer role. Highlight your proficiency in Python, machine learning, and any relevant sports data projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about American football and how your background in data science can contribute to our Sports Modeling team. Be genuine and let your enthusiasm shine through!
Showcase Your Projects: If you've worked on any interesting data science projects, especially those related to sports, make sure to include them in your application. We love seeing real-world applications of your skills!
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It’s the quickest way for us to see your application and get you into the process!
How to prepare for a job interview at DraftKings
✨Know Your Stats
Brush up on your knowledge of American football and the relevant leagues. Be prepared to discuss how your understanding of the game can influence data models and enhance user experiences. Showing genuine passion for the sport will set you apart!
✨Showcase Your Python Skills
Since proficiency in Python is crucial, be ready to demonstrate your coding skills. You might be asked to solve a problem or explain your approach to integrating machine learning models into applications. Practice coding challenges beforehand to boost your confidence.
✨Understand the Machine Learning Lifecycle
Familiarise yourself with the entire machine learning lifecycle, from experimentation to deployment. Be prepared to discuss your past experiences with model development and how you ensure accuracy through testing. This will show that you’re not just a coder but a well-rounded data scientist.
✨Collaboration is Key
Highlight your experience working with cross-functional teams. Discuss how you've collaborated with trading, product, and engineering teams in the past. Emphasising your ability to coach junior data scientists will also demonstrate your leadership potential and team spirit.
