Company 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.

Job Description

Get to Know the Team

Our Data Science Team is committed to developing innovative and highly scalable machine learning algorithms to solve problems in prediction, forecasting, classification, and more, which help to solve business challenges within Grab to enhance the transaction efficiency and reliability of our platform. We are seeking a talented Senior Data Scientist to join our team and play a pivotal role in developing machine learning systems that address key business challenges within Grab. In this role, you'll have the chance to apply cutting-edge technologies and make a meaningful impact on millions of users.

Get to Know the Role

As a Senior Data Scientist, you will play a pivotal role in building LLM-based applications that assist merchants in managing their daily business activities. You will be responsible for providing recommendations, insights, and domain knowledge to resolve business challenges and explore various potential use cases for LLMs to enhance merchant sales. This role offers the opportunity to work with the latest technologies and make a significant impact on our merchants' success.

This role reports to the Senior Data Science Manager, and reports onsite in Singapore Grab office.

The Day-to-Day Activities

•  Deep dive into the big datasets and prepare them for model building and training- Design and build efficient and scalable deep learning/machine learning algorithms  - Evaluate the performance of the algorithms via offline datasets or experiments- Deployment of solutions to production platforms - Contribute to team’s innovation and IP creation- Keep up with the latest literature in deep learning, machine learning- Collaborate with other data scientists, software engineers, and business operation teams

Qualifications

Must Haves

- A PhD or Master's degree in Computer Science, Operations Research, Mathematics or a related field.

- Over 2 years of relevant work experience in data science or a related field.

- Proficiency in programming languages such as Python, PyTorch, SQL, and Spark.

- Strong understanding of data Extracting, Transforming, and Loading (ETL) processes and experience with large data platforms.

- Hands-on experience with machine learning and a passion for exploring their potential applications.

Nice-to-Haves

• Experience in working with food, delivery, and e-commerce data and use cases
• Knowledge of chatbot development and deployment
• Knowledge of RAG (Retrieval Augmented Generation), LLM finetuning etc.
• Strong understanding of data Extracting, Transforming, and Loading (ETL) processes and experience with large data platforms.
• Experience in parallel programming and multithreading
• Knowledge in code optimization techniques

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 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.