Senior Data Scientist

Bangalore, India

Grab

Grab is Southeast Asia’s leading superapp. It provides everyday services like Deliveries, Mobility, Financial Services, and More.

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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 have passion for 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

As a Machine Learning Engineer, you will build scalable and production-grade ML systems across domains like payments, lending, and insurance. You’ll develop predictive models using a blend of machine learning and deep learning techniques. You will engineer high-quality features from diverse data sources, validating model performance on real-world datasets, and implementing pipelines using tools like Python, Spark, and SQL. You’ll collaborate with data scientists, product managers, and engineers to translate our needs into ML solutions. A foundation in ML concepts, hands-on coding ability, and efficiently are key to succeeding in this role.

The Critical Tasks You Will Perform

  • Build and deploy scalable ML models using Python, Spark, and cloud-native tools.
  • Develop data pipelines and feature stores to support model training and inference.
  • 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.
  • 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).
  • Work with cross-functional teams to gather requirements and align ML solutions with product goals.
  • Debug and improve models based on performance drifts or unexpected outcomes.

Qualifications

The Essential Skills You Need

  • This is an individual contributor role suited for professionals with 4 to 7 years of experience.
  • Coding skills in Python for ML model development and pipeline automation
  • Proficiency in Spark, SQL, and distributed data processing
  • Solid grasp of ML concepts like feature engineering, model tuning, and evaluation metrics
  • Experience working with ML/DL libraries (scikit learn, XGBoost, TensorFlow/PyTorch)
  • Familiarity with MLOps tools (Hive, Pyspark, Airflow) for deploying and maintaining models
  • Experience on LLMs, and Generative AI.
  • Work with structured and unstructured data, and build clean, reusable feature pipelines
  • Comfortable with Git and CI/CD best practices
  • Problem-solving and debugging skills
  • Work with cross-functional teams and explain model behaviour

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.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Data Science Jobs

Tags: Airflow CI/CD Data pipelines Deep Learning Engineering Feature engineering FinTech Generative AI Git LLMs Machine Learning ML models MLOps Model training Pipelines PySpark Python PyTorch Scikit-learn Spark SQL TensorFlow Unstructured data XGBoost

Perks/benefits: Career development Medical leave Parental leave Startup environment

Region: Asia/Pacific
Country: India

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