AddressCompany: Future Anthem
Location: Hybrid Working with travel to office in London (Aldgate East)
Salary: £1250 per month
Start Date: 15th July 2024
End Date: September 2024
Process: CV application, Phone interview, Assessment Centre
This is an exceptional opportunity for a collaborative and inquisitive graduate, with a degree in mathematics, statistics, computer science, or another quantitative discipline, to gain hands-on commercial project experience in Big Data and Data Engineering.
Who is the Company?
Future Anthem humanises data with AI to personalise the player experience for everyone. Their market-leading data products and solutions enable their customers to intimately understand their players’ entire journey in real-time, helping them onboard and retain players responsibly.
Future Anthem is the market leader in Game Data Science. They use machine learning to provide automated intelligence to help their customers, games studios and casino operators to grow responsibly with measurable improvements that enhance the casino player experience for everyone. They combine data and technology to offer Game Data Science as a service to the global gambling industry. Trusted by the world’s leading gambling operators and studios (including Bally’s, Big Time Gaming, Blueprint Gaming, and Paddy Power Betfair), Future Anthem was named Data & AI Partner of the Year at the 2022 EGR B2B Awards and Software Rising Star in 2021. Future Anthem was also selected for the highly coveted Tech Nation Applied AI 3.0 Growth Programme.
Future Anthem is a team of intelligent, curious, and talented people passionate about data and results. They offer a positive, flexible working culture and the opportunity to work with the latest technologies in an exciting, constantly evolving industry.
What is the role?
This is an exciting opportunity to gain hands-on commercial project experience within a state-of-the-art cloud computing platform, the Microsoft Azure Framework.
- You will work on their cloud platform, Anthemetrics, which processes 400 million transactions daily. This platform utilises advanced delta lake technology, enabling a Lakehouse architecture with Spark.
- Assist in building, maintaining, and optimising complex data pipelines in a CI/CD development environment, ensuring our products are robust, reliable, and fast.
- Collaborate closely with data science, platform, product, and broader business teams.
Why should you apply?
- This internship offers you the chance to gain real-world experience. Acquire practical knowledge direct involvement in day-to-day operations.
- Learn from industry experts passionate about sharing their knowledge and experience.
- Gain exposure to cutting-edge strategies and tools in a high-tech environment.
- Build valuable connections with professionals across the industry that can propel your career forward.
- Play a crucial role in their team’s success and make a measurable difference in their projects.
- Enjoy your work experience as part of a social and intelligent group of colleagues who value both professional growth and camaraderie.
Who is best suited to apply?
- A 2.1 or above bachelor’s degree in mathematics, statistics, computer science, engineering or similar (A post-graduate master’s degree or PHD is an advantage).
- A candidate who understands and can demonstrate knowledge and experience of general Data Engineering tasks, including data cleaning, data processing, data storage, data pipelines, and code versioning.
- Knowledge of data warehousing concepts and experience with platforms like DataBricks, Amazon Redshift, Google BigQuery, or Snowflake.
- Strong programming skills in any of the following preferred programming languages: Python, Pyspark, Java or Scala.
- Ideally, it would be great if you have knowledge and experience in the following: Azure/ AWS/ Google Cloud.
- You enjoy and have experience working on Big Data problems (ideally in a Spark environment).
- Knowledge/ experience within BI/ Data visualisation (PowerBI/ Tableau).
- You have sound interpersonal skills and enjoy collaborating with others.
- Strong analytical and problem-solving abilities to address complex data-related issues.
