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- 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.
- 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.
- Other info: Collaborate with a skilled team and enjoy a dynamic work environment.
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 in City of London employer: Aristocrat Leisure
Contact Detail:
Aristocrat Leisure Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at industry events. Ask them about their experiences and share your passion for data science – it could lead to a referral!
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Be ready to discuss your experience with R, Python, and SQL, and have examples of your work that showcase your analytical prowess.
✨Tip Number 3
Showcase your communication skills! Practice explaining complex data concepts in simple terms. This will help you stand out as someone who can bridge the gap between data and business needs.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist in City of London
Some tips for your application 🫡
Show Your Analytical Skills: When writing your application, make sure to highlight your experience with data analysis techniques. We want to see how you've used statistics, machine learning, or any other methods to solve real-world problems. Don't just list your skills; give us examples of how you've applied them!
Communicate Clearly: As a Data Scientist, you'll need to communicate complex ideas simply. In your application, aim for clarity and conciseness. Use straightforward language to explain your past projects and findings, so we can easily understand your thought process and impact.
Tailor Your Application: Make sure to customise your application for the role. Refer to the job description and align your experiences with what we're looking for. This shows us that you’ve done your homework and are genuinely interested in joining our team at StudySmarter.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it gives you a chance to explore more about us and what we do before you hit 'send'!
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 previous 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.
