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Senior Data Science Engineer, Sports Modelling

DraftKings

Senior Data Science Engineer, Sports Modelling

DraftKings

London, UK

·

On-site

·

Full-time

·

1mo ago

Required skills

Python

Docker

Kubernetes

Machine Learning

At Draft Kings, 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, Num Py 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.

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About DraftKings

DraftKings

DraftKings is a digital sports entertainment and gaming company that operates daily fantasy sports contests and online sportsbook betting. The company offers mobile and web-based platforms for users to participate in fantasy sports and place sports wagers.

1,001-5,000

Employees

Boston

Headquarters

$12.5B

Valuation

Reviews

3.0

10 reviews

Work-life balance

3.2

Compensation

3.8

Culture

2.8

Career

2.5

Management

2.1

45%

Recommend to a friend

Pros

Good compensation and benefits

Flexible working arrangements

Fun work environment and products

Cons

Poor management and leadership issues

Lack of communication

Limited growth opportunities

Salary Ranges

63 data points

Senior/L5

Staff/L6

Senior/L5 · Lead Security Engineer

1 reports

$178,789

total per year

Base

$137,530

Stock

-

Bonus

-

$178,789

$178,789

Interview experience

5 interviews

Difficulty

3.2

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 80%

Negative 20%

Interview process

1

Application Review

2

Online Assessment

3

Recruiter Screen

4

Technical Phone Screen

5

Final Interview

6

Offer Decision

Common questions

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit