At a Glance
- Tasks: Transform business questions into actionable insights through data analysis and recommendations.
- Company: Join a leading gaming company that values creativity and innovation.
- Benefits: Enjoy competitive pay, career growth, and a supportive team environment.
- Other info: Work in a dynamic, inclusive culture with opportunities for learning and development.
- Why this job: Make a real impact on game success while working with complex data sets.
- Qualifications: Degree in a data-driven field and experience with R/Python and SQL.
The predicted salary is between 36000 - 60000 £ per year.
As one of our Games Data Scientists you will be the business facing masterminds who help turn business questions into actionable insights. You research and analyze player behaviour, and come up with recommendations. Data Scientists do this by listening to team members, understanding context and challenging business ideas. Data Scientists use diverse techniques - frequentist and Bayesian statistics, machine learning, exploratory and explanatory data analysis, causal inference, data visualization, monte carlo modelling, econometric analysis, etc. Such broad requirements call for the ability to learn quickly, work efficiently with peers and communicate data clearly and effectively. Games Data Scientists are true visionaries who support business decisions with data and in-depth analytics.
You will have the opportunity to work with large and complex data sets, with the autonomy to make a huge impact on the success of our games. You will also be working as part of an experienced and highly skilled team of 20 with opportunities to learn and develop.
What you’ll do:
- Discuss with stakeholders requirements for analysis
- Run exploratory data analysis and turn it into questions which can be answered with analytical techniques
- Use simple analytics, statistical or causal inference, machine learning or any other techniques to answer questions and address problems
- Communicate results clearly and effectively
- Take care of unclear and ambiguous requirements
- Communicate complex ideas and analyses in a simple way
- Work independently on complex projects
- Be willing to acquire new skills and learn new methodologies, whether related to stakeholder management, communication or data science
- Be able to use diverse data science tools and approaches
What we’re looking for:
- A degree or equivalent work experience in data driven field
- Ability to use visualization techniques for communicating data and analysis
- Experience of using any of the following to answer business or scientific questions - statistics, mathematics, machine learning, econometrics, causal techniques, monte carlo modelling, etc.
- R/Python experience
- Knowledge and experience of SQL
- Ability to work a minimum of 3 days a week in our central London office.
As part of the Aristocrat family, we share their mission of bringing joy to life through the power of play, with a world-class team who creates top-grossing, leading titles in the social casino genre. We live by our People First principle. Regardless of where, when, or how they work, our team members have opportunities to elevate their careers, and grow alongside us. We take pride in fostering an inclusive culture, where our people are encouraged to be their very best, every day.
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 Scientist employer: Product Madness ??
At Product Madness, we pride ourselves on being an exceptional employer, offering a vibrant work culture that prioritises our People First principle. As a Data Scientist in our central London office, you will have the chance to work with a talented team, engage in meaningful projects, and access numerous opportunities for professional growth while contributing to top-grossing games that bring joy to players worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at Product Madness on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role as a Games Data Scientist.
✨Tip Number 2
Prepare for interviews by brushing up on your data science skills. Be ready to discuss your experience with machine learning, statistics, and data visualisation techniques. Practice explaining complex concepts in simple terms, just like you would to a stakeholder.
✨Tip Number 3
Showcase your projects! If you've worked on any relevant data analysis or machine learning projects, make sure to highlight them during interviews. Bring along examples that demonstrate your ability to turn data into actionable insights.
✨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 Product Madness.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with data analysis techniques like machine learning and statistics. We want to see how you can turn complex data into actionable insights, so don’t hold back!
Tailor Your Application:Take a moment to customise your application for the Data Scientist role. Mention specific projects or experiences that relate to the job description, especially those involving player behaviour analysis or data visualisation.
Keep It Clear and Concise:When communicating your ideas, remember that clarity is key. Use straightforward language to explain your analytical methods and findings, as we value effective communication just as much as technical skills.
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 this exciting opportunity to join our team!
How to prepare for a job interview at Product Madness ??
✨Know Your Data Tools
Make sure you’re well-versed in the data science tools mentioned in the job description, like R, Python, and SQL. Brush up on your skills and be ready to discuss how you've used these tools in past projects or analyses.
✨Prepare for Technical Questions
Expect to face questions about statistical methods, machine learning techniques, and data visualisation. Be prepared to explain your thought process and how you would approach specific business problems using these techniques.
✨Communicate Clearly
Since the role involves communicating complex ideas simply, practice explaining your previous work or projects in layman's terms. This will show that you can bridge the gap between technical data analysis and business insights.
✨Show Your Curiosity
Demonstrate your willingness to learn new methodologies and adapt to changing requirements. Share examples of how you've tackled ambiguous problems in the past and what you did to find clarity and solutions.
