Data Scientist in London

Data Scientist in London

London Full-Time 28800 - 48000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Transform business questions into actionable insights through data analysis and research.
  • Company: Join a leading gaming company with a global presence and a people-first culture.
  • Benefits: Enjoy career growth, a collaborative environment, and the chance to work on exciting projects.
  • Why this job: Make a real impact on game success while working with large, complex data sets.
  • Qualifications: Degree in a data-driven field and experience with R/Python and SQL.
  • Other info: Be part of an award-winning team that values inclusivity and personal development.

The predicted salary is between 28800 - 48000 ÂŁ 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.
Why Product Madness?

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, including Heart of Vegas, Lightning Link, Cashman Casino. With 800 team members across the globe, Product Madness is headquartered in London, with offices in Barcelona, Gdańsk, Lviv, Montreal and a remote team spanning the USA, making us a truly global powerhouse.

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. But don’t just take our word for it. In 2024, we made the Global Inspiring Workplace Awards list, and won a bronze award at the Stevies for Great Employers in the 'Employer of the Year - Media and Entertainment' category.

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 in London employer: GamblingCareers.com

At Product Madness, we pride ourselves on being an exceptional employer, offering a vibrant work culture that prioritises inclusivity and personal growth. As part of the Aristocrat family, our London-based team enjoys the autonomy to make impactful decisions while collaborating with skilled peers in a dynamic environment. With opportunities for career advancement and recognition as a leading workplace, we empower our Data Scientists to thrive and innovate in the exciting world of gaming analytics.
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Contact Detail:

GamblingCareers.com Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist in 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 the company culture; it’s a great way to get insider info and make a lasting impression.

✨Tip Number 2

Prepare for those interviews by brushing up on your data science skills. Be ready to discuss your experience with R/Python, SQL, and any analytical techniques you’ve used. Show us how you can turn complex data into actionable insights!

✨Tip Number 3

Don’t just apply and wait! Follow up on your application through our website. A quick message expressing your enthusiasm can set you apart from the crowd and show us you’re genuinely interested in joining our team.

✨Tip Number 4

Practice communicating complex ideas simply. We love candidates who can break down intricate analyses into digestible bits. Try explaining your past projects to a friend or family member to hone this skill before your interview!

We think you need these skills to ace Data Scientist in London

Data Analysis
Machine Learning
Statistical Analysis
Causal Inference
Exploratory Data Analysis
Data Visualisation
Monte Carlo Modelling
Econometric Analysis
R Programming
Python Programming
SQL
Communication Skills
Stakeholder Management
Problem-Solving Skills
Adaptability

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with data analysis and the specific techniques mentioned in the job description. We want to see how your skills align with what we’re looking for!

Showcase Your Projects: Include examples of past projects where you've used statistics, machine learning, or data visualisation. This helps us understand your practical experience and how you tackle real-world problems.

Communicate Clearly: When writing your application, keep it clear and concise. We value the ability to communicate complex ideas simply, so show us you can do that right from the start!

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. We can’t wait to hear from you!

How to prepare for a job interview at GamblingCareers.com

✨Know Your Data Science Tools

Make sure you’re well-versed in the tools and techniques mentioned in the job description, like R, Python, and SQL. Brush up on your statistical methods and machine learning techniques, as you might be asked to discuss how you've applied them in past projects.

✨Prepare for Stakeholder Discussions

Since you'll be discussing requirements with stakeholders, practice articulating complex ideas in a simple way. Think of examples where you've successfully communicated data insights to non-technical team members, as this will showcase your ability to bridge the gap between data and business needs.

✨Showcase Your Analytical Thinking

Be ready to demonstrate your analytical skills through real-world scenarios. Prepare to discuss how you approach exploratory data analysis and turn ambiguous questions into actionable insights. This will highlight your problem-solving abilities and your understanding of the data science process.

✨Emphasise Your Learning Mindset

The role requires a willingness to learn new methodologies. Share examples of how you've adapted to new tools or techniques in the past. This shows that you're not just skilled but also eager to grow and evolve within the field of data science.

Data Scientist in London
GamblingCareers.com
Location: London

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