Data Analyst

Company Description

Life at  Grab

At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles – the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia.

Job Description

Get to know the Team

The Integrity team acts as guardians of all our users on Grab. We leverage our rich data sets to find solutions to problems ranging from safety to fraud. We’re a hands-on team interested in the end-to-end data life-cycle from analyzing the behavior of our consumers, and identifying any anomalies to building detection and prevention modules for any suspicious activities. If you’re passionate about solving complex problems with immediate real-world impact, we want you!

Get to know the Role

As the Data Analyst in Integrity (Trust, Identity & Safety), you will analyze Grab’s data to develop insights about user behaviors and platform risks. You will translate these insights into recommended actions to combat many different types of fraud. This role will specifically focus on managing fraud risks either related to payments arising due to chargebacks or other system gaps as well as non payment risks related to promotional spends/refunds

The Day-to-Day Activities:

• Analysis of rich user and transaction data to surface patterns, trends, and bugs that help inform Grab’s fraud policies and processes and contribute to fraud prevention mechanisms

• Optimize fraud rules & algorithms to maintain strong fraud detection by rapidly identifying emerging fraud trends through data-driven analysis and developing tactical/strategic fraud rules to address them.

• Perform data/statistical analysis to keep Fraud systems and processes at the cutting edge of fraud detection by identifying areas of potential fraud risk and/or potential opportunity to improve fraud policies, strategies and controls

• Develop and communicate insights and recommended actions to stakeholders to manage risk by contributing toward machine learning models, rules and other detection systems

• Build & maintain dashboards for all stakeholders to provide visibility of key metrics, fraud patterns and detection efficiency

• Be a source of truth for risk metrics in the organization and own their logic as well as monitoring

• Work cross-functionally on managing risk associated with Grab products, processes, and payment methods

• Play the role of a data-driven strategic partner to risk-related decisions in his/her area and is considered to be the subject matter expertise

Qualifications

The Must-Haves:

• 2-5 years of experience as a hands-on analyst in a high-tech company

• A technical degree in Computer Engineering, Information Technology, Data Sciences, Maths or related fields.

• Strong experience in handling large-scale unstructured data. Experience in SQL or other data handling tools, as well as the ability to learn more advanced tools and techniques

• Business intelligence experience using tools such as PowerBI, Tableau, Qlik Sense and Excel.

• Working experience with any of the data analysis tools such as R, Python, SPSS, SAS etc.

• Experience with the application of experimentation and statistical techniques (such as hypothesis testing, probability distributions, regression, decision trees etc.)

• Excellent written and verbal communication skills along with strong training skills.

• Ability to make sound judgment calls independently when presented with difficult decisions, especially when only partial information is available

• Ability to take initiative in a fast-moving environment

The Nice-to-Haves:

• Proficient in RDBMS such as PostgreSQL or MySQL

• Good understanding of the fraud space with hands-on knowledge of fraud, payments and risk

Additional Information

Our Commitment

We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity or sexual orientation and other attributes that make each Grabber unique.