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Senior Data Scientist

Poziții disponibile: O poziție
IT & Software

Get to know the Team

The Data Science (Geo Vision) team at Grab focuses on improving the maps and building map-based intelligence such as localization, routing, travel time estimation, traffic forecasting, that assist various Grab services like transportation, logistics, and pricing. We extensively use Computer Vision, NLP, Information Retrieval, and Text Mining along with conventional machine learning methods on a variety of signals including images, videos, text, sensor readings, GPS probes, etc to understand our locations and road networks. 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 explore and innovate.

Get to know the Role  

We are looking for a senior data scientist to help automate the process of map creation using data science techniques. We believe a successful candidate has very good modern computer vision skills and strong deep learning expertise, but if you believe you have what it takes then we’d love to hear from you either way. This role is required because of the very fast pace of change in the SE-Asia environment impacting deeply the maps. In return, you will get an opportunity to grow in a very challenging environment requiring innovation and creativity.

The Day-to-Day Activities:

  • Understand business needs, identify areas for investigation, translate them to technical problems to be solved

  • Design and develop innovative architectures to address the emerging demands of computer vision and machine learning algorithms.

  • Collaborate across the company, working with software, engineering, and product teams.

  • Deploy solutions into production systems, and also ensure the maintenance and required updates.

The Must-Haves:

  • A solid understanding and experience with Deep Learning, in particular with design, training, evaluation, and optimization of convolutional neural net (CNN) architectures in the context of object detection, segmentation, scene classification, object tracking, OCR, etc.

  • Experience with Python and some of the following libraries: PyTorch, Tensorflow or; NumPy; OpenCV; scikit-learn;

  • Understanding of machine learning methods for classification, regression, and clustering.

  • Linear algebra and matrix transformations

  • A self-motivated learner who keeps himself up-to-date with the current state of computer vision and deep learning techniques/architectures.

  • Able to communicate well in English both verbally and in written communication, as well as convey data insights and results with effective visualizations.

The Nice-to-Haves:

  • Good knowledge of attention and transformer networks would be a strong plus

  • Experience in curating, manipulating, and analyzing large geographical or Spatio-temporal datasets.

  • Experience in designing, deploying or maintaining ML systems in production 

  • Familiarity with Azure Kubernetes Service

  • Familiarity with GIS frameworks and/or databases (e.g. PostGIS).

  • Familiarity with Azure cloud platform

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 super app 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.

Senior Data Scientist
  • Cluj-Napoca

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