Why Work for Us
We Power the Nation.
Make the most of your talents and develop products that can create impact on a national scale. We are an in-house software team, assembled to move with speed and deliver with quality.
We Build Reliable Solutions. For Customers, Company and Country.
You will be part of the Digital Technology Team and together, you will innovate, create, and deploy digital products that will empower more than 3,800 employees within SP Group and improve the quality of life for the 1.5 million commercial, industrial and residential customers that SP Group serves. We build solutions that enable sustainable high quality lifestyles and help consumers save energy and cost, as well as supporting national goals for a sustainable livable city.
Now, imagine the impact you can create.
SP Digital Technology aims to use cutting edge technologies to help SP Group to revolutionize future utility/energy industry by providing better services and more efficient energy solutions to our customers. Data charter consists of data engineering, business intelligence, data science/machine learning teams. We oversee and drive all data and AI initiatives for SP group. It includes the following:
- Build next generation data infrastructure to collect/process/analyze different data from consumers, assets, energy
- Discover the business problems/opportunities and design data-driven solutions to improve operation/business/customer experience
- Uncover the actionable insights for multiple stakeholders to drive business growth
The mission of data team is to drive SP to become data-driven company and create data-driven products. As a data team member, you will be responsible for designing, developing and deploying data-driven solutions to create business value. We are looking for a Data Scientist who will help us discover patterns hidden in large amounts of data and make decisions from different sources. Your primary focus will be in applying data wrangling and machine learning techniques to build high quality anomaly detection, prediction and recommendation systems integrated with our products. You will work closely with customers and data engineers to understand the business requirements, in-house infrastructure and help build solutions for different business users.
What You'll Do:
Nanyang Technological University (NTU) and SP are developing an AI-powered Smart Multi-Energy System (SMES) that will manage and optimise multiple energy sources. In this role, you will work in close collaboration with NTU to deliver and enhance the SMES software solution.
Your primary focus will be on applying data wrangling and machine learning techniques to build high quality anomaly detection for time series IoT sensor data, forecasting models of the energy related information e.g. energy consumption, generation and price, and robust optimisation of energy system e.g. smart grid/microgrid for economic dispatch. You will work closely with customers, data engineers and software engineers to understand the business requirements, in-house infrastructure and help build intelligent solutions.
- Understand business logic from domain experts and come up with reasonable targets for data projects.
- Data wrangling by preprocessing, cleansing, and feature engineering.
- Apply state-of-art machine learning techniques such as RNN, CNN for predictions and anomaly detections.
- Collaborate with a multi-disciplinary team developing a new software platform for energy optimisation systems at a building and district level.
- Improve actual design and test various forecast modules for building load using machine learning.
- Improve actual design and test a unit commitment and economic dispatch software module using electrical, gas and cooling energy mix.
- Define, create and test single and multiple point failure scenario with fall back strategies.
- Deploy, test and commission the new system on test bed buildings.
- Fine tune system to reach performance targets.
- Work closely with researchers, developers and external parties for timely project delivery.
What You’ll Need:
- Experience in machine learning modeling with distributed energy resources such as PV, ESS battery, etc
- Data-oriented personality and software engineering practices.
- Excellent understanding of machine learning models, their pros and cons.
- Experience in Linear and nonlinear optimisation.
- Experience with common data science toolkits such as Python/R.
- Good understanding of statistics, such as distributions, A/B testing, model overfitting/underfitting.
- Domain knowledge in energy metering, billing or building asset management system will be an advantage
- Experience with one of deep learning libraries such as Tensorflow, Keras, Pytorch, CNTK, MXNet etc.
- Master or PhD of Computer Science/Engineering, Applied Mathematics or other engineering related area.
Thank you for your interest in Singapore Power. You will be contacted if you are shortlisted for an interview.