Senior Data Scientist (Supply Planning)

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 will 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 You will be based onsite in Malaysia and reporting to our Senior Data Science Manager. As a Senior Data Scientist, you will look into driver-facing problems and transform these user and business challenges into data science opportunities. You will use big data to derive actionable insights and design solutions. You will develop deep learning, reinforcement learning, and optimization models to solve challenges related to supply repositioning, activation, and incentivization within Grab's marketplace.

The Critical Tasks You Will Perform

You will collaborate with stakeholders to identify the business problems and requirements about driver repositioning, activation and incentivisation.

You will translate the business problems into data science problems, formulate them and design potential solutions.

You will retrieve and analyse relevant data for exploratory analysis, feasibility studies, and solution prototyping.

You will develop and deploy scalable data science solutions, and measure their impact via experiments.

You will build dashboards to keep monitoring the health of DS systems, and continuously maintain and improve the solutions.

What Essential Skills You Will Need

At least 4 years of experience in the relevant field.

Degree in computer science, computer engineering, statistics, data science, applied mathematics, economics, operations research, or other related computational fields

Familiar with developing data processing Extract, Transform and Load pipelines to support data analysis and modeling tasks

Experienced with the machine learning lifecycle. Hands-on experience in developing scalable, end-to-end machine learning solutions.

Understanding of software development lifecycle and engineering practices, experience in writing readable, maintainable and testable code including hands-on experience with unit and model testing

You are proficient in SQL, Python, TensorFlow (or Pytorch) and Spark

Hands-on experience with user profiling and behavioral segmentation for building and deploying recommender systems is a significant plus.

The experience of building real-time streaming applications with Apache Flink will be a plus. Being proficient in Scala or Golang will be a plus.

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.

Balancing personal commitments and life's 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 provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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