At a Glance
- Tasks: Lead a team of data scientists to create innovative data solutions for gaming.
- Company: Join a leading gaming company that values creativity and collaboration.
- Benefits: Competitive salary, mentorship opportunities, and a dynamic work environment.
- Other info: Hybrid work model with at least 3 days in our vibrant London office.
- Why this job: Make a real impact on gameplay and user engagement with cutting-edge data science.
- Qualifications: PhD or MSc in Data Science or related field, with leadership experience.
The predicted salary is between 70000 - 90000 ÂŁ per year.
As the Manager of Data Science, Games Tech, you will be a transformational leader, responsible for guiding and inspiring a dedicated team of data scientists and machine learning engineers. In this role, you’ll drive the creation of groundbreaking data solutions that enhance gameplay, improve user engagement, and optimize business outcomes. As a key partner for multi‑functional teams—including game developers, data analysts, product, and game operations managers—you will use your ML and data expertise to build internal data tools that support decision making and develop customer‑facing data products that enable personalized experiences in our industry‑leading games.
Leadership Responsibilities
- Mentorship & Development: Provide ongoing mentorship, coaching, and professional development opportunities to foster growth and enhance team performance.
- Partnerships: Act as a trusted partner across the organisation, advocating for data‑driven decision‑making and empowering business units to adopt data products.
- Ownership & Accountability: Assume full accountability for the data science project execution to final integration and outcome assessment, ensuring that your team delivers impactful results on time and within scope.
- Insight Communication: Translate sophisticated analytical insights into actionable recommendations, communicating them to the senior leadership team to advise critical business decisions, with the ability to encourage and influence stakeholders.
Technical Responsibilities
- Data Science Best Practices: Drive best practices in A/B‑testing, predictive modelling, user clustering and reinforcement learning, continually setting the standard for data science benefit.
- Engineering Best Practices: Implement the best software engineering practices for internal tools and ML/RL model development, define software architecture standards, implement code review practices, auto‑tests, and improve observability, reproducibility and monitoring of ML/RL solutions.
- Infrastructure Ownership: Own the development of analytical frameworks, including A/B testing (using Bayesian Inference and contextual multi‑armed bandits techniques) and other data science tooling, ensuring scalability, accuracy and reliability across projects.
- Product & Engineering Collaboration: Coordinate integration of analytical solutions into games and platforms, partnering closely with product and engineering to ensure end‑to‑end solution success.
Qualifications and Requirements
- Expertise in clustering, predictive modelling, reinforcement learning, and Bayesian statistics.
- PHD or MSc or equivalent experience in Data Science, Computer Science, Statistics, Physics or related field.
- 5+ years of Data Science experience with a minimum of 2 years in a leadership role.
- Practical experience in software engineering, with a proven track record in design and development of customer‑facing products.
- Experience in ML Ops and deploying machine learning models at scale.
- Proficiency in Python and familiarity with data processing technologies (e.g., Kafka, Spark) and/or cloud platforms (e.g., GCP, AWS, or Azure).
- Ability to work on a hybrid work basis requiring at least 3 days a week in our central London office.
- At this time, we are unable to sponsor work visas for this position. Candidates must be authorized to work in the job posting location for this position on a full‑time basis without the need for current or future visa sponsorship.
Data Science Manager employer: GamblingCareers.com
Contact Detail:
GamblingCareers.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in data science. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your experience—show it! Create a portfolio of projects that highlight your data science skills. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies. But don’t forget to brush up on your soft skills too—communication is key when you're leading a team and working with other departments.
✨Apply Through Our Website
We want to see your application! Make sure you apply through our website to ensure your CV gets the attention it deserves. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Data Science Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Science Manager role. Highlight your leadership experience and technical expertise in data science, as we want to see how you can inspire and guide a team.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how you can drive impactful results. Don’t forget to mention your experience with ML and how you’ve successfully collaborated with cross-functional teams.
Showcase Your Projects: Include examples of your previous work that demonstrate your ability to create data solutions and products. We love seeing real-world applications of your skills, so don’t hold back on sharing your successes!
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 to join our team at StudySmarter!
How to prepare for a job interview at GamblingCareers.com
✨Know Your Data Science Stuff
Make sure you brush up on your knowledge of clustering, predictive modelling, and reinforcement learning. Be ready to discuss how you've applied these techniques in past projects, especially in a leadership role. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Leadership Skills
Prepare examples of how you've mentored and developed your team in previous roles. Highlight specific instances where your guidance led to improved performance or innovative solutions. This is crucial as the role requires you to inspire and lead a dedicated team.
✨Communicate Like a Pro
Practice translating complex data insights into clear, actionable recommendations. You’ll need to demonstrate your ability to communicate effectively with senior leadership and cross-functional teams. Think about how you can make technical jargon accessible to non-technical stakeholders.
✨Familiarise Yourself with Tools and Technologies
Get comfortable discussing your experience with Python, ML Ops, and cloud platforms like GCP or AWS. Be prepared to talk about how you've used these tools to develop customer-facing products and ensure scalability and reliability in your projects.