Senior Data Scientist (Consumer Experience)
Get to Know the Team
The Consumer Experience team aims to provide a great user experience across the app. The data science team works on problems ranging from ranking and recommendations to agentic LLM chatbots and content generation. We're a hands-on team interested in the end-to-end data lifecycle: from wrangling data to understanding the trade-offs between model complexity and deployment in production. We are looking for an experienced Data Scientist with an AI product mindset to help push the frontier of personalization. If you're passionate about solving complex problems with immediate real-world impact, we want you!
Get to Know the Role
You will focus on enhancing a communications targeting system by developing relevance ranking, translation models, and agentic marketing content generation projects. You will report to the Senior Data Science Manager and this role is based in Grab One North Singapore office. If you are ready to shape how millions of users interact with our platform, apply today!
The Critical Tasks You Will Perform
- You will enhance communication targeting systems by developing relevance ranking algorithms, translation models, and agentic marketing content generators.
- You will analyse quantitative and qualitative data to develop a deep behavioural understanding of our users and inform personalization strategies.
- You will collaborate with product, marketing, and engineering teams to manage the end-to-end lifecycle of designing, implementing, and deploying ML and LLM models.
- You will build and test robust models, develop data pipelines, and establish observability and evaluation frameworks for systems in production.
- You will leverage Generative AI (GenAI) and AI coding assistants to accelerate model development, automate data wrangling, and streamline your evaluation workflows.
What Essential Skills You Will Need
- At least 4 years of experience in data science or machine learning, supported by a Master's degree in Computer Science, Engineering, Mathematics/Statistics, or a related technical discipline.
- Proficiency in programming languages such as Python, R, or Java, along with experience in data pipeline development and ETL processes.
- Experience with predictive modelling algorithms (e.g., logistic regression, neural networks, decision trees, heuristic models) and their trade-offs in production.
- Hands-on experience with ML/DL frameworks and libraries, including Scikit-Learn, Pandas, XGBoost, TensorFlow, or PyTorch.
- Practical experience managing the end-to-end ML lifecycle, including feature selection, hyper-parameter optimization, and model validation.
- You have experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.
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.
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.
View our location
Nestled in the vibrant heart of Singapore is Grab's Global HQ! Take a tour of our office here, meet some of our teams and find out what it’s like to work in this vibrant cosmopolitan.
Meet the Data Science team
Our Data Science team is on a mission to create delightful experiences for our users. Every day, they dive into the data to uncover new and intelligent ways to deliver hyperlocal services and solutions to our communities in Southeast Asia.
Every small step of innovation at Grab has an instant impact on hundreds of millions of active users. Nothing is more exciting than facing challenges, exploring uncertainties and advancing the state-of-the-art in artificial intelligence.
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My journey has been fueled by a passion for making a tangible impact through data. Having been a Senior Data Scientist at GrabFin, and now a Lead Data Scientist at Grabads, I found the perfect opportunity to work with massive datasets, which has led to greater impact in my work.
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I get to bring data to life throughout the product journey – from scoping problems and setting metrics to experimenting and tweaking things for the better. It's not just about numbers; it's about actively shaping and improving our products every day.
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The Application Process
What can you expect when you apply for a role at Grab? Here’s what our hiring process looks like.
Step 1: Apply.
We have a range of open roles from Marketing to Engineering and everything in between. Find the one that’s best for you and show us why you’re our next teammate.
Step 2: Getting to know you.
Next, you’ll have a video or phone interview with one of our recruiters to chat about you, the role, and your past work experiences.
Step 3: Testing, testing… 123.
Some roles might require assessments and/or a technical competency interview. For other roles, there might be an additional interview – speak with your recruiter for application details.
Step 4: Is it a culture match?
Finally, we’ll find out how we fit together, if your career vision aligns with our mission, how you embody the 4 H's, and your working style and personality.
