Lead Data ScientistChina
Life at Grab
At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia.
Get to know the Team
Grab is Southeast Asia’s leading super-app. We provide everyday services such as deliveries, mobility, financial services, enterprise services and others to millions of users across the region. The Fulfillment tech family is one of the pillars enabling Grab to out-serve our consumers and partners in different businesses and marketplaces across Southeast Asia. We are working on high throughput, real-time distributed systems that use sophisticated machine learning techniques to solve hundreds of millions of requests per day. Our mission is to offer the best-in-class products and experiences to our driver partners as to increase adoption and engagement of our services. Improve driver partner opportunities and efficiency in order to fulfill customer orders without fail, rain or shine. And to create efficient marketplaces by determining an optimal price that is both sustainable and loved by our partners and consumers.
Get to know the Role
We are looking for a lead data scientist to join the team. We believe a successful candidate has solid understanding of statistical modeling, machine learning and deep learning, tracking record of cleaning/processing big data and building deep machine learning models, experience working on deploying ML and DL models in production systems, excellent soft skills to communicate with stakeholders.
In return, you will have the opportunity to work on big data to extract insights and establish solutions. You will develop statistical, machine learning, and/or deep learning models to solve ETA problems inside Grab’s marketplace and deploy them at scale.
The Day-to-Day Activities
Conduct thorough analyses of time durations among major events of orders by examining historical data and design effective feature engineering methods accordingly.
Develop and improve data processing ETL pipelines to efficiently support data analysis, model training and model serving works.
Develop accurate, robust, and cost-efficient machine learning models for the prediction of time durations among major events of orders.
Create technical documents outlining the methodologies and findings, and communicate solutions to business stakeholders in a clear, non-technical manner. This ensures that stakeholders have a comprehensive understanding of the models and services being developed.
Take charge of project management, collaborate closely with the technical teams to deploy the machine learning models in a production environment, ensuring their smooth integration into the system.
Communicate and collaborate with country teams to implement and roll out the model services effectively. This involves coordinating efforts, addressing any concerns or challenges, and ensuring consistent execution across different markets.
At least Master Degree in computer science, statistics, mathematics, operation research, economy, physics, software engineering or related fields.
3+ years of experience in one or more of the following areas: statistical modeling, generic machine learning, deep learning, and causal inference.
Experience translating complex business problems into ML/AI formulations.
Proficiency in Python, Tensorflow/PyTorch, SQL, Spark. Experience in writing efficient SQL query and readable, maintainable and testable codes.
Experience developing production quality Pipelines to automate the model tuning and deployment.
Excellent communication skills to manage the stakeholders.
Proficiency in English writing and speaking skills.
PhD degree in computer science, statistics, mathematics or related field.
Candidates with expertise in streaming data using frameworks like Apache Flink will have an added advantage.
Experience with distributed systems and cloud services such as AWS, GCP, and Azure is highly valued.
The ability to autonomously explore new ideas and learn new skills to accomplish tasks is a crucial attribute we seek in potential candidates.
We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity or sexual orientation and other attributes that make each Grabber unique.
Grab is an equal opportunity employer. We owe our success to the talents of our globally-diverse team and the varying perspectives they add to our thriving community.
Grab does not accept unsolicited resumes sent by recruiting agencies. Please do not forward resumes to our job postings, Grab employees or other parts of the business. Grab will not be liable to pay any fees to agencies for candidates hired as a result of unrequested resumes.