Senior Data Scientist (Deliveries & ACE)

Rocket Lab; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

Join a forward-thinking company that is revolutionizing the delivery and dining experience in Southeast Asia. As a Data Scientist, you will leverage your expertise in machine learning and data analysis to solve real-world challenges and enhance user satisfaction. Collaborating with cross-functional teams, you'll design and deploy AI models that optimize delivery efficiency and personalize user experiences. This role offers a unique opportunity to contribute to innovative solutions while working in a dynamic environment that values your well-being and professional growth.

Benefits

Term Life Insurance

Comprehensive Medical Insurance

Flexible Benefits Package (GrabFlex)

Parental Leave

Birthday Leave

Volunteering Leave

Grabber Assistance Programme

Qualifications

• 3+ years of experience analyzing large datasets for insights.
• Strong knowledge of machine learning and optimization algorithms.

Responsibilities

• Analyze datasets to uncover insights about user behaviors.
• Forecast shopping needs and optimize delivery strategies.

Skills

Machine Learning

Data Analysis

Python

Deep Learning

Statistical Analysis

AI Solutions

Education

Master's Degree in Machine Learning

Bachelor's Degree in Computer Science

Tools

TensorFlow

PyTorch

Scala

Job 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.

Get to Know the Team

The Deliveries & ACE Data Science team is at the heart of Grab's delivery and omnicommerce business. We create, deploy, and refine AI/ ML models to enrich the user experience across Grab’s food ecosystem—from meal deliveries to restaurant reservations. We are committed to enhancing user satisfaction, promoting growth, and optimising platform efficiency by solving unique challenges in delivery, demand forecasting, and personalised dining experiences.

Get to Know the Role

As a Data Scientist specialising in Deliveries and Dine-out/ Reserve vertical, you will report into the Senior Data Science Manager and work onsite in Grab One North Singapore office. You will help leverage data and AI to solve real-world challenges and drive impactful decisions. You will span advanced analytics, machine learning model development, and collaboration with cross-functional teams to enhance the delivery and dining-out experience for our users.

The Critical Tasks You Will Perform

• You will analyse large-scale datasets (geospatial, behavioural, transactional) to uncover actionable insights about user shopping behaviours and patterns within delivery and dine-out/ reserve services.
• You will use AI to forecast shopping needs, preferences, and cancellation probabilities, improving personalised recommendations and enhancing service reliability.
• You will predict spikes in delivery demand and trends in restaurant reservations using advanced machine learning models.
• You will optimize visibility strategies to match user demand with supply, ensuring efficient network performance and reducing instances of unfulfilled orders.
• You will enable smart targeting of distinct user segments to drive demand generation efforts.
• You will design, test, and deploy AI models, refining them through A/B testing and monitoring their real-time performance.
• You will work with product managers, engineers, analysts, designers, and operations teams to scale and implement impactful solutions across the platform.
• You will contribute to the advancement of the team by driving innovation and creating intellectual property in AI/ ML space for deliveries and omnicommerce.

What Essential Skills You Will Need

• You have a Master Degree in Machine Learning, Statistics, Applied Mathematics, Computer Science, Economics, Operations Research, or a related field
• You have at least 3 years of experience analysing large-scale datasets to extract business insights (e.g. geospatial, behavioural, and transactional data).
• You have knowledge in machine learning, deep learning, optimization algorithms, and data mining techniques. Familiarity with ML frameworks like TensorFlow or PyTorch is essential for building and refining predictive models.
• You have experience in fine-tuning LLM models and developing use cases based on LLM (e.g. for recommendation systems or user personalization).
• You are competent in Python or Scala to design and implement machine learning pipelines.
• You can forecast, shape, and generate demand using AI-powered strategies within delivery, booking, or e-commerce verticals.
• You have experience applying AI solutions to real-world problems, in deliveries, booking industries, or e-commerce applications.

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.