Lead Data Scientist
Lead Data Scientist
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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 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 realtime 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
Youll develop credit risk scoring models for consumer loans including PD LGD and collection models. Youll work with alternative data sources to boost model signal and accuracy. Your role will involve full ownership of the endtoend model lifecyclefrom building and validation to deployment and maintenance. Youll 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 inmarket 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 tradeoffs 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 tradeoffs between model performance and our needs.
- Strong problemsolving mindset is critical for success in this role.
Additional Information :
Life at Grab
We care about your wellbeing 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 LoveallServeall (LASA) volunteering leave
- We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through lifes 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.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
