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- Tasks: Lead data science projects and develop advanced models to drive business forward.
- Company: Join DraftKings, a tech leader shaping the future of AI in gaming.
- Benefits: Competitive salary, innovative work environment, and opportunities for professional growth.
- Why this job: Be at the forefront of AI innovation and make a real impact on customer experiences.
- Qualifications: Experience in data science, machine learning, and proficiency in Python or R.
- Other info: Collaborative team culture with mentorship opportunities and career advancement.
The predicted salary is between 36000 - 60000 £ 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.
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 drive 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:
- Lead data science projects from conception to deployment, ensuring high-quality and timely delivery.
- Develop and implement statistical models and machine learning algorithms to solve complex business problems.
- Collaborate with cross-functional teams to integrate data science solutions into production systems.
- Mentor junior data scientists and provide guidance on best practices and methodologies.
- Communicate technical findings and insights to internal stakeholders to support data-driven decision-making.
- Assist with the adoption of data-driven strategies into the trading processes.
- Assist with the design, development, maintenance, and testing strategy of trading automation solutions, ensuring alignment with overall business objectives.
What You’ll Bring:
- Proven experience in data science, with a strong foundation in machine learning and statistical modeling.
- Proficiency in programming languages such as Python or R, and experience with data manipulation and visualization tools.
- Demonstrated ability to break down complex problems into manageable tasks and deliver high-quality results.
- Excellent problem-solving skills and the ability to work collaboratively in a team environment.
- Experience in developing and implementing automated trading or decision-making systems is highly desirable.
- Experience with Kubernetes and Kafka are desirable.
- Experience with Databricks is desirable.
- Experience with experimentation is desirable.
- 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.
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
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at DraftKings. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving machine learning and statistical models. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past projects and how you've tackled complex challenges. We want to see your thought process!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining our team at DraftKings. Let’s build the future together!
We think you need these skills to ace Senior Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Science Engineer role. Highlight your proficiency in Python or R, and any experience with machine learning and statistical modelling. We want to see how you can contribute to our innovative team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and data science, and how your background makes you a perfect fit for DraftKings. Let us know how you envision shaping the future with us!
Showcase Your Projects: If you've worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. We love seeing practical applications of your skills, especially those involving automated trading or decision-making systems.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at DraftKings!
How to prepare for a job interview at DraftKings
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning and statistical modelling skills. Be ready to discuss specific projects you've worked on, the algorithms you used, and the impact they had. This is your chance to show how your expertise can drive DraftKings' data science initiatives forward.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex business problems in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers. Highlight your ability to break down challenges into manageable tasks and deliver high-quality results.
✨Collaboration is Key
Since you'll be working with cross-functional teams, be ready to share examples of how you've successfully collaborated in the past. Discuss how you’ve integrated data science solutions into production systems and how you communicate technical findings to non-technical stakeholders.
✨Get Familiar with Their Tech Stack
Do some homework on the tools and technologies mentioned in the job description, like Kubernetes, Kafka, and Databricks. If you have experience with these, be sure to mention it. If not, show your willingness to learn and adapt to new technologies that can enhance trading automation solutions.
