Lead Data Science Engineer

Lead Data Science Engineer

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead innovative data science projects, creating impactful sports models and applications.
  • Company: Join DraftKings, a trailblazer in sports and entertainment technology.
  • Benefits: Enjoy a dynamic work environment with opportunities for growth and collaboration.
  • Why this job: Tackle exciting challenges while shaping the future of responsible gaming and sports experiences.
  • Qualifications: Experience in data science, Python programming, and leading teams is essential.
  • Other info: A passion for sports and a relevant degree are highly valued.

The predicted salary is between 43200 - 72000 £ per year.

We are defining what it means to build and deliver the most extraordinary sports and entertainment experiences. Our global team is trailblazing new markets, developing cutting-edge products, and shaping the future of responsible gaming. Here, "impossible" isn’t part of our vocabulary. You’ll face some of the toughest but most rewarding challenges of your career. They’re worth it. Channeling your inner grit will accelerate your growth, help us win as a team, and create unforgettable moments for our customers.

Our team comprises sports modelling experts and data science technologists, coming together to develop innovative DS products that deliver incremental value on the Sportsbook platform at DraftKings. As part of this role, you will be a creative thinker, utilizing data, machine learning, and software development skills to craft high-impact best-in-class sports models that grow the business.

What you’ll do as a Lead Data Science Engineer:

  • Research and implement DS applications in Python
  • Create statistical and machine learning models and integrate them into DS applications
  • Work with and help develop our MLOps pipeline
  • Data engineering of data assets to assist in DS application development
  • Writing production quality code to deploy and run models in a sportsbook
  • Create automatic tests to ensure accuracy and reliability of DS applications
  • Collaborate closely with product, developers, QAs and delivery leads to move projects from ideation to development and deployment
  • Test that data flows work as expected and that DS applications are well integrated in larger business context
  • Build advanced analytics tools for sportsbook product teams
  • Coach and support more junior data scientists within the team

What you’ll bring:

  • Experience as the expert on a data science team where you were responsible for all aspects of data science technical projects, including development and deployment, and then monitoring of how those applications perform in production
  • Experience leading and coaching other data scientists
  • Strong understanding of object-oriented programming principles with Python
  • Understanding of different database technologies, including relational and non-relational databases
  • Experience implementing ML automation, MLOps principles and related tools
  • AWS experience will be considered an asset
  • Experience with typical DevOps flows, such as containerisation (e.g. Docker) and monitoring (e.g. ELK, Grafana)
  • Experience with Kubernetes and Kafka is very desirable
  • Knowledge of web frameworks (e.g. Flask, Django) and HTTP APIs is desirable
  • Keen interest in sports
  • Understanding of Sportsbook products will be considered an asset
  • PhD, Masters or Bachelor’s degree in STEM fields
  • Excellent communication & organisation skills with the ability to articulate key business information quickly and effectively

Join Our Team

We are 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.

Lead Data Science Engineer employer: DraftKings Inc.

At DraftKings, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our Boston headquarters is not just a workplace; it's a hub for creativity where you can grow your skills alongside industry experts in data science and sports modelling. With a commitment to employee development and a focus on delivering extraordinary experiences, we empower our team to tackle rewarding challenges that shape the future of responsible gaming.
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Contact Detail:

DraftKings Inc. Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Lead Data Science Engineer

✨Tip Number 1

Familiarise yourself with the latest trends in data science and machine learning, especially as they relate to sports analytics. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.

✨Tip Number 2

Showcase your experience with MLOps and automation tools by preparing examples of past projects where you've successfully implemented these practices. Being able to discuss your hands-on experience will set you apart from other candidates.

✨Tip Number 3

Network with professionals in the sports tech industry, particularly those who work with data science. Attend relevant meetups or webinars to build connections that could lead to referrals or insider information about the role.

✨Tip Number 4

Prepare to discuss how you would approach building a data science application for a sportsbook. Think through the entire process from ideation to deployment, and be ready to share your thought process and any relevant experiences.

We think you need these skills to ace Lead Data Science Engineer

Python Programming
Statistical Modelling
Machine Learning
MLOps Implementation
Data Engineering
Production Quality Code Writing
Automated Testing
Collaboration Skills
Object-Oriented Programming
Database Technologies (Relational and Non-Relational)
DevOps Practices
Containerisation (e.g. Docker)
Monitoring Tools (e.g. ELK, Grafana)
Kubernetes
Kafka
Web Frameworks (e.g. Flask, Django)
HTTP APIs
Strong Communication Skills
Coaching and Mentoring

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with Python and machine learning. Emphasise any leadership roles or coaching experiences you've had, as these are key for the Lead Data Science Engineer position.

Craft a Compelling Cover Letter: In your cover letter, express your passion for sports and how it aligns with the company's mission. Discuss specific projects where you've implemented MLOps principles or developed statistical models, showcasing your creativity and problem-solving skills.

Showcase Technical Skills: Clearly outline your technical skills related to object-oriented programming, database technologies, and DevOps flows. Mention any experience with AWS, Docker, Kubernetes, or Kafka, as these will strengthen your application.

Highlight Collaboration Experience: Since the role involves working closely with product teams and other developers, include examples of past collaborations. Describe how you’ve successfully moved projects from ideation to deployment, demonstrating your ability to work in a team environment.

How to prepare for a job interview at DraftKings Inc.

✨Showcase Your Technical Skills

Be prepared to discuss your experience with Python, machine learning models, and data engineering. Bring examples of projects where you've implemented these skills, especially in a sports or gaming context.

✨Demonstrate Leadership Experience

Since the role involves coaching junior data scientists, share specific instances where you've led a team or mentored others. Highlight how you foster collaboration and support within a technical team.

✨Understand the Business Context

Familiarise yourself with DraftKings' Sportsbook products and the broader gaming industry. Be ready to discuss how your work can create value for the business and enhance customer experiences.

✨Prepare for Problem-Solving Questions

Expect to tackle technical challenges during the interview. Practice explaining your thought process clearly and logically, especially when discussing MLOps principles and DevOps flows like containerisation.

Lead Data Science Engineer
DraftKings Inc.
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