Lead Data Scientist
Bangalore, India
Grab
Grab is Southeast Asia’s leading superapp. It provides everyday services like Deliveries, Mobility, Financial Services, and More.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
GrabFin is an aggregate of FinTech businesses spread across 6 countries in S.E. Asia, in the Lending, Payments and Insurance domains. We are excited to provide innovative financial services to all participants of the Grab Ecosystem be it our Drivers, Consumers or Merchants. Our products are built on fundamental market insights combined with data science and engineering to bring the best product market fit across the cross section of our user base. This understanding of our ecosystem combined with world class engineering execution continues to create tremendous value for our customers.
The data scientist will work in a relatively flat team structure with an independent goal of building and manage critical data science models daily. You can expect to solve hard technical problems and grow into an expert on both batch and real-time Data Science use cases. You will have experience with technology and data science.
You will be reporting to Senior Manager, Data Science.
This role is onsite based in Bangalore.
Get to know the role
You'll develop credit risk scoring models for consumer loans, including PD, LGD, and collection models. You'll work with alternative data sources to boost model signal and accuracy. Your role will involve full ownership of the end-to-end model lifecycle—from building and validation to deployment and maintenance. You’ll collaborate with business, risk, and operations teams to shape solutions and influence product strategy with your insights. This is an individual contributor role suited for professionals with 8+ years of experience.
The Critical Tasks You Will Perform
- Build predictive models using a mix of machine learning and traditional analytics methods to segregate between Good vs Bad borrowers
- Build Machine learning & Deep learning models to estimate losses from of a given portfolio.
- Validate models on new datasets, based on in-market performance.
- Engineer predictive features from internal data assets to build refined customer profiles. Identify external data assets to bring into the model mix.
- Drive model governance by collaborating with risk policy, compliance, and audit teams to ensure adherence to regulatory expectations.
- Identify model gaps or performance drifts and lead model refresh cycles.
- Present findings to senior leadership with clear articulation of risk trade-offs and growth.
- Translate model insights into strategic recommendations (e.g., policy changes, pricing levers, customer targeting strategies).
- Solve previously unsolved analytics problems using best in class data analytics and machine learning methodologies.
Qualifications
The Essential Skills You Need
- 8+ years of experience.
- Strong understanding of credit business – lifecycle of a loan, collections process, and credit KPIs like NPL, ECL.
- Expert in building machine learning and predictive models in Python and Spark is an absolute must.
- SQL, Presto, Hive proficiency.
- Sound knowledge of machine learning concepts. Illustrative machine learning concepts/methods are: Bagging, Boosting, Regularisation, Online Learning, Recommendation Engines
- Experience with LLMs, and Generative AI
- Experience with model deployment pipelines – using MLFlow, Airflow, or other MLOps tools.
- Demonstrated experience building machine learning models
- Understand the trade-offs between model performance and our needs.
- Strong problem-solving mindset is critical for success in this role.
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.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Credit risk Data Analytics Deep Learning Engineering FinTech Generative AI KPIs LLMs Machine Learning MLFlow ML models MLOps Model deployment Pipelines Python Spark SQL
Perks/benefits: Career development Medical leave Parental leave
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