Business Intelligence Analyst, Payments (APAC)
2d ago

There is no love sincerer than the love of food - George Bernard Shaw

Do you love food and convenience put together? Then you will definitely love foodpanda!

foodpanda (small f’) is the world’s favourite way to order food online from the comfort of your home or office. Whether it’s getting your hands on your favourite pasta, kebab or pizza, we believe that no one should have to suffer from hunger attacks ever again.

However, this doesn’t happen without some really awesome people. We are looking for a Business Intelligence Analyst to support our growing Regional Payments team here in Singapore, as part of an international team of highly talented and motivated people.

To thrive in this role, you will need the technical expertise to navigate a complex and ever-changing data infrastructure as well as the ability to communicate effectively and persuasively to a non-technical audience.

What's on your menu :

  • Work closely with internal stakeholders to understand business challenges and recommend solutions across the complex range of products and processes
  • Apply mathematical and statistical methods to solve complex business problems
  • Develop regionally relevant, scalable and future-proof solutions
  • Be a steward of good data practices - robust documentation, versioning, playbooking, processes, and knowledge sharing
  • Identify and communicate project priorities on a regular basis to internal stakeholders across 11 countries
  • Understand foodpanda's data infrastructure and work with stakeholders globally to report and troubleshoot data quality issues
  • Support ad-hoc data requests
  • What do you bring to the table :

  • A Bachelors / Masters degree in an analytical field such as Statistics, Mathematics, Computer Science, Engineering, Economics, Business or equivalent business experience
  • 2-5 years of experience of working as a data analyst in the payments / fintech space
  • Excellent analytical skills and knowledge of analytics tools required (SQL, Excel, Tableau, Python, or R)
  • Proven experience extracting data from structured and unstructured data sources using SQL
  • Hands-on experience with troubleshooting performance issues and fine-tuning SQL queries
  • Experience with geographical data or GIS tools such as QGIS and Kepler are a plus
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