At a Glance
- Tasks: Develop advanced sports models and data-driven solutions to enhance user experiences.
- Company: Join DraftKings, a leading tech company shaping the future of AI in sports.
- Benefits: Competitive salary, gaming license support, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on collaboration and career advancement.
- Why this job: Be part of an innovative team transforming the sports betting landscape with AI.
- Qualifications: Degree in a relevant field and proficiency in Python and machine learning.
The predicted salary is between 60000 - 80000 £ 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.
The Crown Is Yours
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. 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. 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, NumPy methods 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.
- Demonstrated passion for sports 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.
Join Our Team
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, Sports Modelling employer: Dormont Manufacturing Co
At DraftKings, we pride ourselves on being at the forefront of innovation in the sports and gaming industry. Our vibrant work culture fosters collaboration and creativity, providing employees with ample opportunities for professional growth and development. Located in Boston, we offer a dynamic environment where your passion for sports and technology can thrive, making us an exceptional employer for those looking to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Science Engineer, Sports Modelling
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Dormont Manufacturing Co!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Science Engineer, Sports Modelling at Dormont Manufacturing Co.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Dormont Manufacturing Co.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Science Engineer, Sports Modelling at Dormont Manufacturing Co, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Science Engineer, Sports Modelling
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Dormont Manufacturing Co, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Dormont Manufacturing Co. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Dormont Manufacturing Co
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Dormont Manufacturing Co!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
