Data Analyst, Grab Financial

  • Grab
  • Singapore
  • Sep 13, 2019

Job Description

Get to know our Team:
At GrabFinancial we believe that upholding trust and integrity is at the heart of doing business with all our customers. GrabFinancial Risk team is a dynamic regional group that focuses on protecting transactions of millions of Grab customers across Southeast Asia. The team employs cutting-edge digital trust, customer-centric solutions, and expert talents from all across the industry to ensure fraud and abuse are kept outside the door.

Get to know the Role:

  • Be an integral part of Grab Financial fraud prevention framework across Southeast Asia
  • Optimise risk actions and processes to achieve highest customer acceptance while minimising losses.

  • Perform data mining and research techniques to identify fraudulent behaviours.

  • Create data-driven strategies to prevent or limit account take-over, credit card fraud, merchant risk, collusion schemes, syndicated fraud attacks.

  • Perform forensics, deep dives, and forecasting, on various risk or business matters.

  • Implement actions such as configurations and business rules.

  • Report facts to seniors and managers in a clear, concise and factual manner.

  • Provide inputs to relevant policies and procedures, as needed.

  • Ensure necessary databases are available and maintained for research and regulatory purposes.

The must haves:

  • Problem-solving, positive and constructive attitude is a must.

  • Comfort in dealing with ambiguity and operating in fast-changing, unstructured environments.

  • Structured, factual and data-driven. Ability to deep dive into data and elaborate clear findings.

  • Sound knowledge in e-payments and fintech, and related fraud, desired but not absolutely required.

  • Proficient in RDBMS such as PostgreSQL or MySQL.
  • Ninja level in Excel.
  • Python / R is a plus.
  • Meticulous attention to detail and double-checking as a second nature.
  • Ability to work independently and to seek guidance when required.
  • Hands-on experience with fraud detection tools e.g. scoring models and rules engines is a plus.
  • Knowledge of credit card scheme rules and banking processes is a plus.
  • Excellent verbal and written communication in English and ideally one local SEA language.