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For Companies At a Glance
- Tasks: Lead data science projects, develop models, and analyze large datasets to enhance our products.
- Company: DraftKings is a leader in digital sports entertainment, shaping the future of responsible gaming.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and mentorship.
- Why this job: Tackle rewarding challenges while driving innovation in a collaborative team culture.
- Qualifications: Experience in data science, machine learning, and proficiency in Python or R required.
- Other info: Join a publicly traded company and receive support for obtaining necessary gaming licenses.
The predicted salary is between 43200 - 72000 ÂŁ per year.
We’re 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.
The Crown Is Yours
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 Senior Data Science Engineer
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Create statistical and machine learning models and integrate them into DS applications
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Collect and engineer sports data assets to assist in model development
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Implement the sports models and pricing engines in Python
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Create automatic tests to ensure model and pricing engine accuracy
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Collaborate closely with product, developers, QAs and delivery leads to move projects from ideation to deployment
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Test that data flows work as expected and that models are well integrated in larger business context
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Research the different sport’s specifications and rules
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Coach and support more junior data scientists within the team
What You’ll Bring
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Highly proficient in at least one programming language, ideally Python
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Experience of building statistical or machine learning models for multiple sports
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Understanding of data science and statistical modelling principles
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Experience with Kubernetes and Kafka are desirable
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Knowledge of MLOps principles and related tools will be considered an asset
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Keen interest in sports, particularly tennis
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Self-learner who is open to learning new things
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Familiarity with version control concepts
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Understanding of object-oriented programming principles
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Understanding of Sportsbook products will be considered an asset
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PhD, Masters or Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, Engineering, or related field
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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Senior Data Science Engineer employer: DraftKings
Contact Detail:
DraftKings Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Science Engineer
✨Tip Number 1
Familiarize yourself with the latest trends in data science and machine learning, especially those relevant to the gaming industry. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Showcase your experience with low latency systems and automated trading solutions. Be prepared to discuss specific projects where you've implemented these technologies, as they are crucial for the role at DraftKings.
✨Tip Number 3
Network with professionals in the sports entertainment and gaming sectors. Engaging with industry experts can provide insights into the company culture and expectations, which can be beneficial during the interview process.
✨Tip Number 4
Prepare to discuss how you've mentored junior data scientists in the past. Highlighting your leadership skills and ability to communicate complex concepts will set you apart as a candidate who can contribute to team growth.
We think you need these skills to ace Senior Data Science Engineer
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights your experience in data science, machine learning, and statistical modeling. Use specific examples that demonstrate your ability to lead projects and deliver high-quality results.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sports and entertainment technology. Discuss how your skills align with the responsibilities of the Senior Data Science Engineer role and how you can contribute to DraftKings' mission.
Showcase Technical Skills: Clearly outline your proficiency in programming languages like Python or R, and mention any experience with tools such as Kubernetes, Kafka, or Databricks. Highlight any relevant projects where you've implemented automated trading systems.
Prepare for Technical Questions: Be ready to discuss your technical findings and insights during interviews. Prepare to explain complex problems you've solved and how you collaborated with cross-functional teams to integrate data science solutions.
How to prepare for a job interview at DraftKings
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like Python or R. Highlight specific projects where you developed statistical models or machine learning algorithms, and be ready to explain the impact of your work.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your problem-solving skills. Prepare examples of complex problems you've tackled in the past, detailing how you broke them down into manageable tasks and the results you achieved.
✨Emphasize Collaboration
Since collaboration is key in this role, share experiences where you worked with cross-functional teams. Discuss how you integrated data science solutions into production systems and the importance of teamwork in achieving project goals.
✨Prepare for Technical Discussions
Be ready to communicate technical findings clearly to non-technical stakeholders. Practice explaining your insights and methodologies in a way that highlights their relevance to business decisions, as this will be crucial in your role.
