Data Scientist

Location: Hong Kong

*** Mention DataYoshi when applying ***

Siemens Mobility Limited

If you really want to make a difference – make it with us

Mobility goes digital. Siemens Mobility is the world’s leading provider of mobility solutions that enable the efficient, safe and environmentally friendly transport of people and goods – and help improve the quality of everyday life for millions of people in Hong Kong. Driven by innovation, we develop intelligent solutions for the increasing digitalization of the transport sector. Our range of offerings includes rail vehicles, rail automation, road traffic management systems and rail electrification. Our data-driven services offer customers value-added that is unique, and not only in our industry. We are looking for the best talent to shape the technology of the future. Come build your career in one of the best companies in the world! Welcome to visit:

Your skills and experience

  • We develop data- / AI-driven solutions for even smarter management of road traffic (e.g. AI-traffic light control) and rail infrastructure, as well as intermodal mobility. To do this, we work closely with our customers, partners and Siemens departments, with agile methods and rapid prototyping in line with the lean startup concept.
  • In this environment, you can use your expertise in Data Analytics and Machine Learning to help shape ecologically sustainable smart traffic for the future along with underlying functions for autonomous driving.
  • In our growing team you will develop innovative solutions for exploratory data analysis in highly complex data structures.
  • Your aim is to identify unknown relationships in data from traffic management systems, traffic light systems, vehicles and other third-party sources in order to create cutting-edge solutions.
  • You will create reusable analytical models, operationalizing them in the analytics platform and visualizing the results.
  • You will contribute to the successful realization of modern data analytics and machine learning within our projects.
  • You will work directly with customers and project partners.
  • Delivering presentations to stakeholders from the business will be another element of your role.

Individuals who meet the following requirements or possess the equivalent combination of competence and experience are invited to apply:

  • Degree in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Physics, Electrical Engineering, Industrial Engineering, Bioinformatics, Economics) or equivalent practical experience from a reputed institute.
  • Grass-root experience of at least 2 years in solving complex problems and driving actionable insights from structured and unstructured large datasets.
  • Solid understanding and experience in using statistical models and machine learning algorithms such as Forecasting, Classification, Clustering, and Optimization algorithms.
  • Good programming skills (Python, R or similar) and experience with database languages (SQL).
  • Experienced in using cloud services from AWS/GCP/Azure.
  • Solid understanding of BI tools such as Tableau/Spotfire.
  • Candidates with data engineering and ETL experience will also be considered.
  • Hands-on experience with one or more of the following will be an added advantage:
    • Hands-on experience in training and deploying CNN, RNN using frameworks like TensorFlow/PyTorch on GPUs.
    • Experience working on image processing and computer vision problems experience using OpenCV, object detection and tracking models.
    • Clear understanding and ability to implement algorithms using ONNX and TensorRT.
  • Closely follow latest developments in artificial intelligence and be an early adopter of disruptive trends/technologies.
  • You have experience in multidisciplinary projects and working with customers, and you have a proven track record of implementing big data projects.

Siemens Mobility

Company: Siemens Mobility Limited

Experience Level: Experienced Professional

Job Type: Full-time

*** Mention DataYoshi when applying ***

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