Data Scientist - GrabFin

Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

Get to Know the Team

At GrabFin, we operate as a cluster of FinTech businesses spanning across six countries in Southeast Asia. We're dedicated to delivering financial solutions for all members of the Grab Ecosystem, including drivers, consumers, and merchants. Our offerings are crafted with deep market insights, and we leverage data science and engineering excellence to create meaningful value for our customers. Our team, though structured with room for independent mandates, values collaboration to ensure the best outcomes for our users.

Get to Know the Role

Reporting to Senior Manager, Data Science, you'll embark on a journey to devise predictive models that cater to various business needs like credit risk, customer engagement, collections, purchase propensity, fraud detection, and identity verification within Grab Financial. Your expertise in building and validating data science models will be pivotal. The role allows for the exploration of both batch and real-time data science applications, and you'll independently handle numerous intricate technical challenges.

You will be fully onsite at Singapore's Grab HQ office at One-north.

The Critical Tasks You Will Perform

• You will develop predictive models to solve business needs, utilizing a strong understanding of user behaviors.
• You will manage the full lifecycle of data science models, from development to deployment and maintenance.
• You will collaborate with business, risk, and operations teams to inform solutions and propose product changes.
• You will engineer predictive features from internal data and assess external data sources for model enhancement.
• You will create dashboards to monitor model performance and key performance indicators.
• You will handle complex analytical problems independently or as part of a team.

Qualifications

What Essential Skills You Will Need

• Bachelor's or Master's Degree in Machine Learning, Statistics, Applied Mathematics, Computer Science, Economics, Operations Research, or a related field
• Proficiency in machine learning and predictive model development, especially using Python and Spark, is essential.
• Solid understanding of machine learning concepts such as Bagging, Boosting, Regularisation, and Recommendation Engines.
• SQL, Presto, and Hive skills for data manipulation and query execution.
• 1+ years of experience with Large Language Models (LLMs) and Generative AI is beneficial.
• Strong ability in feature engineering for various data types.
• Demonstrated competency in building effective machine learning models and understanding business trade-offs.

Additional Information

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 enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.