Get to Know the Team
The Integrity team is dedicated to safeguarding our users on Grab. We are building a centralized, unified Risk and Compliance technology platform using Grab's proven risk and compliance tech, GrabDefence. We use our datasets and advanced AI capabilities to address critical challenges, from ensuring safety and preventing fraud to achieving regulatory compliance. We are involved in the entire data lifecycle, including analyzing user behavior, identifying financial crime anomalies, and developing detection and prevention modules across user onboarding and transaction journeys.
Get to Know the Role
Reporting to the Senior Analytics Manager in the Integrity team, you will be a key analytics partner in operationalizing the Unified Risk Platform that manages risk across the Grab Ecosystem. You will conduct deep-dive analysis on user behaviors, product funnels, and transaction patterns to identify potential risks and new fraud typologies on our partner platforms. Your data-driven insights will directly guide the design of risk detection strategies, the optimization of shared AI/Machine Learning models, and the implementation of crucial risk controls to safeguard a diverse user base from multiple types of fraud and financial crime.
This role is based onsite in our Petaling Jaya office.
The Critical Tasks You Will Perform
- You will be the subject matter expert in using data to analyze fraud loss, business/product performance, and the effectiveness of risk controls across different Grab business verticals.
- You will lead the identification of new fraud and risk patterns, developing data-driven rules and strategies to address potential risks using advanced methods like Graph-Based Detection.
- You will conduct statistical analyses to ensure the accuracy and efficiency of detection systems, maintaining data and rule integrity.
- You will architect automated self-serve capabilities for stakeholders to monitor key risk metrics, attack patterns, and the efficiency of fraud/AML detection systems.
- You will collaborate with Grab business teams to support data extractions, audits, and compliance requirements, ensuring all necessary data is provided for assessments.
- You will conduct experiments to evaluate the effectiveness of risk controls and recommend improvements based on findings.
What Essential Skills You Will Need
- At least 4 years of experience in data-related or quantitative fields.
- A Bachelor's Degree in disciplines such as Analytics, Statistics, Software, Mathematics, Economics, Computer Science, or Engineering.
- Proficiency in SQL, Presto, ETL, Power BI, Python, and Excel.
- Experience with the application of experimentation and statistical techniques (such as hypothesis testing, probability distributions, regression, decision trees).
- Intermediate understanding and early hands-on exposure towards Gen AI/LLM's including prompt engineering, query optimization, automated insight generation
- Proficiency in Feature Engineering (SQL, Spark) to build data inputs for models, with a clear focus on data utility and feature logic rather than data pipeline ownership.
- Desirable: Understanding of the risk management, fraud and compliance space (e.g. AML, eKYC) in digital ecosystems
Life at Grab
We care about your well-being at Grab, here are some of the global benefits we offer:
- We have your back with Term Life Insurance and comprehensive Medical Insurance.
- With GrabFlex, create a benefits package that suits your needs and aspirations.
- Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
- We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
- Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours
What We Stand For At Grab
We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.