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- Tasks: Lead a team of data scientists to create innovative data solutions for gaming.
- Company: Join a leading gaming company focused on data-driven decision-making.
- 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 in the gaming industry with cutting-edge data science.
- Qualifications: PhD or MSc in relevant field and 5+ years of data science 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 in London employer: GamblingCareers.com
Contact Detail:
GamblingCareers.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those that highlight your leadership and technical expertise. This will give hiring managers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate insights effectively to various stakeholders.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Science Manager in London
Some tips for your application 🫡
Show Your Passion for Data Science: When writing your application, let your enthusiasm for data science shine through! Share specific examples of how you've used data to drive decisions or improve outcomes in your previous roles. We love seeing candidates who are genuinely excited about the field.
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Science Manager role. Highlight relevant experiences that align with the job description, especially your leadership skills and technical expertise. This shows us you’ve done your homework and understand what we’re looking for.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language and avoid jargon unless it’s necessary. We appreciate candidates who can communicate complex ideas simply, as this is a key part of the role when translating insights for stakeholders.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the position. Plus, it makes the whole process smoother for everyone involved.
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 your insights relatable and impactful.
✨Familiarise Yourself with Their Tech Stack
Research the technologies mentioned in the job description, like Python, Kafka, and cloud platforms. If you have experience with these tools, be prepared to discuss how you've used them in your work. Showing that you're already familiar with their tech stack can give you a significant edge.