Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Science Engineer, American Football

DraftKings, Inc.
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist London, United Kingdom

Head of Data Science Technology (Product, Engineering, Design) · London ·

Head of Data Science

Senior Data Engineer (Distributed Data Processing)

Overview

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


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

Join Our Team

We\u2019re 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\u2019t worry, we\u2019ll guide you through the process if this is relevant to your role.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.