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For Companies At a Glance
- Tasks: Lead data science projects, develop models, and analyse large datasets to enhance our products.
- Company: DraftKings is a leader in digital sports entertainment, innovating the gaming industry.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and mentorship.
- Why this job: Join a trailblazing team, tackle exciting challenges, and make a real impact in sports entertainment.
- Qualifications: Proven data science experience, strong machine learning skills, and a relevant degree required.
- Other info: You may need a gaming license; we’ll support you through the process.
The predicted salary is between 43200 - 72000 £ 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 Science Engineer on our Trading Intelligence Team, you will play a pivotal role in driving our data science initiatives forward. You will develop solutions that power our platform and dive our business forward. You will be responsible for developing advanced models and algorithms, analyzing large datasets, and providing actionable insights to enhance our product offerings and business operations.
What You\\\’ll Do as a Senior Data Science Engineer
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Lead data science projects from conception to deployment, ensuring high-quality and timely delivery.
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Develop and implement statistical models and machine learning algorithms to solve complex business problems.
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Collaborate with cross-functional teams to integrate data science solutions into production systems.
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Mentor junior data scientists and provide guidance on best practices and methodologies.
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Communicate technical findings and insights to internal stakeholders to support data-driven decision-making.
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Assist with the adoption of data-driven strategies into the trading processes
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Assist with the design, development, maintenance, and testing strategy of trading automation solutions, ensuring alignment with overall business objectives
What You\\\’ll Bring
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Proven experience in data science, with a strong foundation in machine learning and statistical modeling.
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Proficiency in programming languages such as Python or R, and experience with data manipulation and visualization tools.
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Demonstrated ability to break down complex problems into manageable tasks and deliver high-quality results.
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Excellent problem-solving skills and the ability to work collaboratively in a team environment.
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Experience in developing and implementing automated trading or decision-making systems is highly desirable
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Experience with Kubernetes and Kafka are desirable
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Experience with Databricks is desirable
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Experience with experimentation is desirable
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A Bachelor\\\’s degree in a relevant field such as Computer Science, Statistics, Mathematics, or a related discipline.
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
Familiarise yourself with the latest trends in data science and machine learning, especially focusing on LSTM-based models and probabilistic graphical models. This knowledge will not only help you during interviews but also demonstrate your commitment to staying ahead in the field.
✨Tip Number 2
Engage with the data science community by attending meetups or webinars related to automated trading systems and decision-making processes. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Showcase your experience with tools like Kubernetes, Kafka, and Databricks through personal projects or contributions to open-source initiatives. Having practical examples to discuss can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss how you've successfully led data science projects from conception to deployment. Be ready to share specific examples of challenges faced and how you overcame them, as this will highlight your leadership and problem-solving skills.
We think you need these skills to ace Senior Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, machine learning, and statistical modelling. Emphasise any projects where you've developed LSTM-based models or worked with probabilistic graphical models.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sports and entertainment technology. Mention specific examples of how your skills can contribute to DraftKings' mission and the role of a Senior Data Science Engineer.
Showcase Technical Skills: Clearly outline your proficiency in programming languages like Python or R, and any experience with tools such as Kubernetes, Kafka, or Databricks. Provide examples of how you've used these skills in past projects.
Prepare for Technical Questions: Anticipate technical questions related to data science methodologies and problem-solving approaches. Be ready to discuss your experience with automated trading systems and how you approach complex data challenges.
How to prepare for a job interview at DraftKings
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning and statistical modelling in detail. Highlight specific projects where you've developed LSTM-based models or worked with probabilistic graphical models, as these are crucial for the role.
✨Demonstrate Problem-Solving Abilities
Expect to face complex problem scenarios during the interview. Practice breaking down these problems into manageable tasks and articulate your thought process clearly. This will showcase your analytical skills and ability to deliver high-quality results.
✨Emphasise Collaboration Experience
Since the role involves working with cross-functional teams, share examples of how you've successfully collaborated with others in past projects. Discuss how you communicated technical findings to non-technical stakeholders to support data-driven decision-making.
✨Prepare for Questions on Automation and Trading Systems
Given the focus on trading automation solutions, be ready to discuss any relevant experience you have in developing automated trading systems. Familiarise yourself with tools like Kubernetes and Kafka, as well as your approach to integrating data science solutions into production systems.
