Singapore, Singapore
April 10, 2022
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Job Description:
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
Data Science, GEO - Traffic team at Grab focuses on building world-class map services and machine learning applications such as travel time estimation, activity recognition, high-precision indoor / outdoor positioning and computer vision on mobile. These applications enhance Grab's consumer experience on transport, deliveries, logistics and optimize our platform efficiency.
We extensively use various data science and machine learning approaches to solve different geo-spatial related business problems, such as tree boosting techniques, deep neural networks, graph processing, personalization and recommendation models, detection and segmentation of computer vision models etc.. These technologies are applied on a variety of signals including GPS probes, sensor readings, images, etc. to build strong map service capabilities.
We also support the development of innovative, highly scalable, models through deep research and advanced analysis so that we make our products intelligent and delight our customers. We foster a culture where we enjoy raising the bar constantly for ourselves and others, and that strongly supports the freedom to ideate, innovate, invent and create impact on day-to-day lives of millions of people.
Get to know the Role
As a Senior Data Scientist for our DS-Traffic teams, you would be responsible for designing, experimenting and implementing machine learning models / algorithms to solve geo-spatial related problems and build reliable map services. Typical workflow includes building data pipelines, training machine learning models, rolling out services and tracking key metrics for the success of the project. You will be working closely with lead, teammates and other stakeholders to complete tasks in time independently.
You would get to utilise deep learning, data mining, computer vision along with classical machine learning methods on a variety of signals including imagery, transactions, GPS probe signals and sensor data. You would not only develop the right tools and models for the data you are handling, but you would get to invent innovative ways of enhancing the quality and quantity of upstream data, as well as creatively acquire new complementary signals to boost system performance.
The Day-to-Day Activities:
- Collaborate with stakeholders to identify business requirements and outcome
- Translate moderately complex business problems into data science problems.
- Develop data pipelines, data science models to solve identified problems.
- Design appropriate experiments to validate finding or test hypotheses.
- Gain insights from data and results
- Define success business metrics for the overall project to show improvements
- Provide on-going tracking and monitoring of performance of the strategy recommended, especially during experiment and rollout.
- Design and deploy enhancements and fixes to systems as needed.
- Document analysis, methodology, algorithms, results and insights in a clear and logical manner.
- Present and depict the rationale of findings in easy to understand terms for the business.
- Communicate and work with business subject matter experts
- Assist in solving assigned parts of problems in projects.
The Must-Haves:
- You have a degree in computer science, electrical/computer engineering, or mathematics/statistics. Master’s / PhD degree preferred.
- You typically have 1-5 years related experience in data science.
- You typically have 1-5 years experience in programming languages, such as Python, Java, C++, Spark and experience in manipulating large datasets.
- You are familiar with the principles behind the state-of-the-art machine learning, deep learning, data mining, algorithmic foundations of optimization, probability and statistics.
- You are good in one or more of the following domains: predictive modeling, time-series modeling, road network / traffic modeling, positioning modeling, computer vision modeling.
- You are good in one or more of the following programming languages: Python, Scala, Golang, C++.
- You are good in relational databases and have hands-on experience coding in SQL.
- You are a self-motivated, independent learner, and capable of completing good quality work on time.
- You have good communication and interpersonal skills.
- You are able to collaborate with multiple stakeholders.
The Nice-to-Haves:
- Experience in the O2O platform company, map service company or other related geo-spatial domain.
- Experience in ETA, traffic prediction, routing algorithm, positioning algorithm or mobile-side computing is a very desirable plus.
- Experience in processing data and building ML models using distributed computing frameworks (e.g. Spark).
- Know the modern data pipeline and warehousing stacks, e.g. Hive, Livy, Azkaban/Airflow, PrestoDB, ElasticSearch, Kafka stream processing, Flink etc.
- Familiarity with cloud platforms like AWS or Azure
Our Commitment
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.
About Grab
Grab is the leading superapp platform in Southeast Asia, providing everyday services that matter to consumers. Today, the Grab app has been downloaded onto millions of mobile devices, giving users access to over 9 million drivers, merchants, and agents. Grab offers a wide range of on-demand services in the region, including mobility, food, package and grocery delivery services, mobile payments, and financial services across 428 cities in eight countries.
Join us today to drive Southeast Asia forward, together.
