Get to know our Team:
Grab’s lending business (GFSA – Grab Financial Services Asia) is a recent addition to Grab’s
array of product and service offerings focused on extension of Micro credit to drivers, agents
and merchants in Grab’s ecosystem. GFSA team is a combination of strong talent pool in its
Regional Hub (Singapore) and deep local market operators across its focus markets. We are
incredibly excited about the opportunity ahead of us. We are looking to put together the best
possible combination of business build drive, industry expertise and local market depth as
part of our team. GFSA team is responsible for end to end conceptualization, design,
development, execution and ongoing management of all lending activities in its focus
markets and segments.
Get to know the Role:
- Develop a deep behavioral understanding and intuition of our passengers and drivers, especially in the space of how they would violate our policies and game our systems
- Manage and own the entire end-to-end lifecycle of designing models, working with Engineering for implementation, to maintenance and enforcement
- Generate multivariate statistical models to identify latent factors, preventive and preemptive capabilities that the trust framework requires
- Interface with business & operation teams to formulate solutions & product changes informed by your findings
- Work independently or in a team to solve complex problem statements
The day-to-day activities:
- Translate these intuitions into actionable, creative insights that produces heuristic or classification models to identify and take down those who violate our Terms of Services
- Test and validate these insights via rapid experimentation and deployment
The must haves:
- Proficient in RDBMS such as PostgresQL or MySQL; and statistical programming in languages like R, Python, Java, C++ or SAS
- Experience in ETL, feature selections, modeling, model validation and conducting data analyses using R, SQL, Python or any JVM languages
- Deep understanding and implementation experience of predictive modeling algorithms such as logistic regression, neural networks, forward propagation, decision trees and heuristic models, with familiarity dealing with trade offs between model performance and business needs
- Experience in interfacing with other teams and departments to deliver impact solutions for organisation
- Self-motivated, independent learner, and enjoy sharing knowledge with team members
- Detail-oriented and efficient time manager in a dynamic and fast-paced working environment
Really nice to haves:
- Deep understanding of the fraud space with hands-on knowledge of fraud, payments and risk, especially on tech products
- Experience in geospatial databases or graph databases
- Recent programming experience in a production environment
- Experience in Scala or PySpark on distributed systems
- Interest in working with MapReduce technologies (such as Hadoop / Spark)
- Familiarity with Python Scikit Learn, Panda or Spark ML/Mllib is a plus
