Senior Data Scientist
Senior Data Scientist
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Job Description
Get to Know the Team
GrabFin is empowering financial inclusion across Southeast Asia by combining market insights advanced data science and engineering excellence. We build innovative financial services for the Grab ecosystem catering to our Drivers Consumers and Merchants across 6 countries. Our team blends expertise in Lending Payments and Insurance to create tremendous value for our customers. At GrabInsure part of GrabFin we focus on insurance products tailored for our diverse user base with cutting-edge technology and data-driven problem-solving.
Get to Know the Role
Reporting to the Senior Manager Data Science you will work on crafting scalable production-grade machine learning systems to support innovative insurance products. Youll leverage diverse datasets to develop predictive models and features ensuring performance matches real-world needs. Youll collaborate with cross-functional teams including product managers and engineers turning business needs into robust machine learning solutions. This role offers a great opportunity to have a tangible impact on our insurance offerings and is a fully on-site role at Grabs Singapore One-North office.
The Critical Tasks You Will Perform
- Build production-ready machine learning models leveraging Python Spark and cloud-native tools.
- Construct and automate efficient data pipelines and feature stores for model development and deployment.
- Engineer features from both structured internal data and supplemental external data sources to refine customer profiling.
- Analyze and validate model performance using real-world datasets ensuring in-market accuracy.
- Identify and preempt performance drifts leading updates or refresh cycles for models.
- Present data insights and predictions to senior leadership explaining trade-offs and business implications.
- Work closely with product managers and engineers to meet product goals through well-aligned ML solutions.
- Provide actionable recommendations based on model findings such as adjustments to policies or customer engagement strategies.
- Debug and enhance models addressing unexpected outcomes or operational challenges.
Qualifications :
What Essential Skills You Will Need
- 4 to 7 years experience in using Python for developing machine learning models and automating supporting pipelines.
- Expertise in distributed data processing tools like Spark and SQL.
- Thorough understanding of machine learning concepts such as feature engineering hyperparameter tuning and model evaluation metrics.
- Hands-on experience with machine learning and deep learning libraries including Scikit-learn XGBoost TensorFlow and PyTorch.
- Familiarity with MLOps tools (e.g. Hive PySpark Airflow) for model deployment and lifecycle management.
- Capacity to work with structured and unstructured data while designing efficient reusable data pipelines.
- Knowledge of Git and CI/CD best practices for streamlined development workflows.
- Strong analytical skills to debug solve problems and improve model performance.
- Optional but beneficial: experience with LLMs Generative AI or insurance-specific data science tasks.
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 lifes challenges.
- Balancing personal commitments and lifes 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.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
