At a Glance
- Tasks: Transform business questions into actionable insights through data analysis and recommendations.
- Company: Join a leading gaming company with a focus on innovation and teamwork.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborate with a skilled team and enjoy a dynamic work environment.
- Why this job: Make a real impact on game success by analysing player behaviour and trends.
- Qualifications: Degree in a data-driven field and experience with R/Python and SQL.
The predicted salary is between 28800 - 48000 £ 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.
- 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
A degree or equivalent work experience in data driven field is required. Ability to use visualization techniques for communicating data and analysis is essential. 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 and knowledge and experience of SQL are also necessary. Ability to work a minimum of 3 days a week in our central London office is required.
Data Scientist employer: Aristocrat Leisure
As a Data Scientist at our company, you will thrive in a dynamic and innovative environment that values collaboration and creativity. With a strong focus on employee growth, we offer extensive learning opportunities and the chance to work with cutting-edge data science techniques while making a significant impact on our games' success. Our central London office fosters a vibrant work culture where your insights are valued, and your contributions directly influence business decisions.
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 or alumni from your university who work in data science. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning or data visualisation. This is your chance to demonstrate how you turn data into actionable insights.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex data concepts in simple terms, as this is key to being a successful Games Data Scientist.
✨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.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Your Data Passion:When writing your application, let us see your enthusiasm for data science! Share specific examples of how you've used data to solve problems or make decisions. We love seeing candidates who are genuinely excited about turning data into actionable insights.
Tailor Your Application:Make sure to customise your application to highlight the skills and experiences that align with our job description. Mention your experience with techniques like machine learning, causal inference, or data visualisation. This shows us you understand what we're looking for!
Keep It Clear and Concise:We appreciate clarity in communication, so keep your application straightforward. Avoid jargon unless it's relevant, and focus on making complex ideas easy to understand. Remember, we want to see how well you can communicate data insights!
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 role. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Aristocrat Leisure
✨Know Your Data Science Tools
Make sure you’re well-versed in the tools mentioned in the job description, like R, Python, and SQL. Brush up on your statistical techniques and be ready to discuss how you've used them in past projects. This shows you’re not just familiar with the theory but can apply it practically.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems using data analysis. Think about how you would approach a business question, what data you would need, and which analytical techniques you would apply. Practising these scenarios will help you articulate your thought process clearly.
✨Communicate Complex Ideas Simply
Since you'll need to explain your findings to stakeholders, practice breaking down complex analyses into simple terms. Use examples from your past work where you successfully communicated insights to non-technical team members. This will demonstrate your ability to bridge the gap between data and business.
✨Show Your Willingness to Learn
Highlight your eagerness to acquire new skills and methodologies. Share instances where you’ve taken the initiative to learn something new, whether it’s a new programming language or a data science technique. This attitude is crucial in a fast-evolving field like data science.
