Head of Data Science, Games Tech — Lead ML & Data Tools

Head of Data Science, Games Tech — Lead ML & Data Tools

Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
Aristocrat

At a Glance

  • Tasks: Lead a team to create innovative data solutions that enhance gameplay and user engagement.
  • Company: Join a leading games tech 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 central London office.
  • Why this job: Make a real impact in the gaming industry with cutting-edge data science.
  • Qualifications: PhD or MSc in Data Science or related field, with 5+ years of experience.

The predicted salary is between 80000 - 100000 £ 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. You will also develop customer-facing data products that enable personalized experiences in our industry-leading games.

What you'll do

  • Key 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.
  • Key Technical Responsibilities
    • Data Science Best Practices: Drive best practices in A/B-testing, predictive modelling, user clustering and reinforcement learning, to continually set the standard on data science benefit.
    • Engineering Best Practices: Be responsible for the implementation of the best software engineering practices for internal tools and ML/RL model development, define software architecture standards, implement code review practices, auto-tests, 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.

What we need from you

  • 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, proven track record in design and development of the 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.

Travel Expectations: None

Additional Information: 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.

Head of Data Science, Games Tech — Lead ML & Data Tools employer: Aristocrat

As a leading employer in the gaming industry, we pride ourselves on fostering a dynamic and inclusive work culture that prioritises innovation and collaboration. Our central London location offers employees access to a vibrant city life while providing ample opportunities for professional growth through mentorship and development programmes. Join us to be part of a team that not only values your expertise but also empowers you to create impactful data solutions that enhance user experiences in our cutting-edge games.

Aristocrat

Contact Details:

Aristocrat Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Head of Data Science, Games Tech — Lead ML & Data Tools

Network Like a Pro

Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars. Building relationships can lead to job opportunities that aren’t even advertised yet.

Show Off Your Skills

Don’t just talk about your experience; showcase it! Create a portfolio of your projects or contributions to open-source initiatives. This gives potential employers a tangible sense of what you can bring to the table.

Ace the Interview

Prepare for interviews by practising common questions and scenarios related to data science and leadership. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your achievements.

Apply Through Our Website

Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.

We think you need these skills to ace Head of Data Science, Games Tech — Lead ML & Data Tools

Leadership
Mentorship
Data Science Best Practices
A/B Testing
Predictive Modelling
User Clustering
Reinforcement Learning

Some tips for your application 🫡

Show Your Passion for Data Science:When writing your application, let your enthusiasm for data science shine through! We want to see how your experience aligns with our mission to create groundbreaking data solutions that enhance gameplay and user engagement.

Tailor Your Application:Make sure to customise your CV and cover letter to highlight relevant experiences that match the job description. We love seeing how your skills in clustering, predictive modelling, and reinforcement learning can contribute to our team!

Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so make sure to communicate your insights and experiences effectively, especially when discussing your leadership roles and technical expertise.

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 this exciting opportunity in our central London office.

How to prepare for a job interview at Aristocrat

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 Insights Clearly

Practice translating complex data insights into actionable recommendations. You’ll need to demonstrate your ability to communicate effectively with senior leadership and other stakeholders. Think about how you can make your insights relatable and impactful.

Familiarise Yourself with Tools and Technologies

Get comfortable discussing the data processing technologies and cloud platforms mentioned in the job description, like Kafka, Spark, GCP, AWS, or Azure. Being able to talk about your practical experience with these tools will set you apart from other candidates.