Senior Data Scientist (Supply Planning)

GrabTaxi Holdings Pte. Ltd.; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

GrabFlex benefits

Parental leave

Birthday leave

LASA volunteering leave

Grabber Assistance Programme

Job summary

GrabTaxi Holdings Pte. Ltd. in Singapore is seeking a Senior Data Scientist to translate driver and marketplace problems into data science challenges.

You will leverage big data to derive insights and build models for supply repositioning, activation, and incentives within Grab's marketplace. You will report to the Senior Data Science Manager and work onsite at Grab One North, collaborating with stakeholders across product, operations, and engineering to deploy scalable DS solutions and monitor

Qualifications

• 3+ years of relevant experience in data science or related field.
• Degree in CS, CE, statistics, data science, applied mathematics, economics, OR, or related field.
• Experience ETL pipelines to support modelling and optimisation tasks.
• Experience translating business problems into OR models using LP, MILP, NLP.
• Experience designing and implementing heuristics or meta-heuristics (e.g., Genetic Algorithms).
• Knowledge of software development lifecycle and testing practices.

Responsibilities

• Collaborate with stakeholders to identify driver repositioning, activation and incentivisation requirements.
• Translate business problems into data science problems and design potential solutions.
• Retrieve and analyse data for exploratory analysis and feasibility studies.
• Develop and deploy scalable data science solutions and measure impact via experiments.
• Build dashboards to monitor health of DS systems and continuously improve solutions.

Skills

ETL pipelines

Optimization modelling

LP/MILP/NLP

Heuristics e.g. Genetic Algorithms

Software testing (unit & model)

Education

Degree in CS/CE/Statistics/DS/Applied Math/OR

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

Grab's Supply Planning team is dedicated to enhancing the experience of our driver partners, ensuring they can drive smartly and effectively. As the data science team, we'll leverage AI technologies to provide driver partners with strategic, data-driven instructions and incentives, so as to optimize the supply utilization given the various market conditions.

Get to Know the Role

As Senior Data Scientist, you'll look into the driver-facing problems and transform these user / business problems into DS problems. You'll use big data to derive actionable insights and design solutions. You'll develop deep learning, reinforcement learning, and optimisation models to solve challenges related to supply repositioning, activation, and incentivisation within Grab's marketplace.

This position will be reporting to the Senior Data Science Manager and be based onsite in Grab One North Singapore office.

The Critical Tasks You Will Perform

• You'll collaborate with stakeholders to identify the business problems and requirements about driver repositioning, activation and incentivisation.
• You'll translate the business problems into data science problems, formulate them and design potential solutions.
• You'll retrieve and analyse relevant data for exploratory analysis, feasibility studies, and solution prototyping.
• You'll develop and deploy scalable data science solutions, and measure their impact via experiments.
• You'll build dashboards to keep monitoring the health of DS systems, and continuously maintain and improve the solutions.

What Essential Skills You Will Need

• You have at least 3 years of relevant experience and a Degree in computer science, computer engineering, statistics, data science, applied mathematics, economics, Operations Research (OR), or other related computational fields.
• You are familiar with developing Extract, Transform, and Load (ETL) data pipelines to support complex mathematical modelling and optimisation tasks.
• You are familiar with the mathematical optimisation lifecycle, possessing hands-on experience translating business problems into rigorous OR models using Linear Programming (LP), Mixed-Integer Linear Programming (MILP), or Non-Linear Programming (NLP).
• You have experience designing and implementing custom heuristics or meta-heuristics (e.g., Genetic Algorithms) for computationally expensive, large-scale optimisation problems where exact solutions are not feasible.
• You have good understanding of the software development lifecycle and engineering practices, with experience writing readable, maintainable, and testable code (including hands-on experience with unit and model testing).

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.