About Envision Digital:
Envision Digital is focused on bringing technology solutions to the sustainability challenge . Its world-class AIoT technology helps governments and companies across the world accelerate progress toward a net zero future and improve their citizens’ quality of life. Having established itself as a leading solutions provider for intelligent renewable energy generation, consumption efficiency and smart flexible storage, it has extended its capabilities beyond energy to enable and optimise applications notably in smart cities, smart buildings and estates, smart infrastructures, e-mobility and smart plants.
EnOS™, Envision Digital’s proprietary AIoT operating system, connects and manages more than 100 million smart devices and 200 gigawatts of energy assets globally, while its growing ecosystem of more than 350 customers and partners spans 10 industries and includes Accenture, Amazon Web Services, GovTech Singapore, Keppel Corporation, Microsoft, Nissan, PTT, Sonnen, Solarvest and Total. The company has around 700 employees and 12 offices across China, France, Japan, Germany, Norway, the Netherlands, the United Kingdom, and the United States, with headquarters in Singapore.
1. Develop appropriate machine learning (ML) models for time-series forecasting and fault detection problems in renewable energy domain and AIoT regime. Employ analytical approaches on real problems faced by our key clients.
2. Use Envision AI platform to design ML pipelines and deliver efficient algorithm models for algorithm products or services provided for internal and external clients. Properly design model evaluation process and testing process to ensure model performance.
3. Closely work with DS team with a strong team spirit. Collaborate with stakeholder teams with efficient communication skills.
1. Experienced in machine learning algorithms on general regression and classification models, including traditional models (Random Forest, GBDT, SVM, etc) and deep-learning models (CNN, RNN/LSTM, etc).
2. Minimum experience: 5 years
3. Familiar with time series analysis, regression, clustering and classification algorithms and their principles, mastering the techniques of feature engineering, hyper-parmater tuning and model evaluation principle.
4. Proficient in Python and familiar with tools like pandas, sklearn, numpy, etc. Familiar with at least one popular deep learning framework, such as Tensorflow, Keras, or PyTorch.
5. Strong abilities in learning, communication, and analyzing and solving problems. An awesome team player with a strong sense of responsibility and great enthusiasm for work.