Data Science Intern (2024)
A global AIoT software leader in Net Zero, Envision Digital is committed to becoming the world’s leading net zero technology partner for enterprises, governments, and cities to accelerate progress and improve their citizens’ quality of life.
EnOS™, Envision Digital’s proprietary AIoT operating system, connects and manages more than 110 million smart devices and 360 gigawatts of energy assets globally. Envision Digital’s growing ecosystem of more than 360 customers and partners spans 10 industries and includes Accenture, Amazon Web Services, GovTech Singapore, IBM, Keppel Corporation, Microsoft, Nissan, PTT, Solarvest, Total and ST Engineering. The company has close to 900 employees and 12 offices across the United Kingdom, France, Germany, the Netherlands, Norway, Japan, Thailand, China, and the United States, with headquarters in Singapore.
For more information, please visit www.envision-digital.com/
Data Science Intern
We are looking for Data Scientist interns who will work with the team to develop algorithms package to deliver data-analytical services and products for our clients on top of EnOS platform. The ideal candidate should be adept of using a variety of ML/AI models, from traditional statistical learning models to deep-learning models, to address various data-driven requirements. They should have the experiences in data exploration, model design, implementation, and tuning and delivery modeling results to stakeholders. They must be comfortable working with a wide range of stakeholders and functional teams. Last but not least, the passion for data science is strongly preferred especially for those who are interested in applying the cutting-edge AI/ML technologies to improve daily productivity.
- Work with team and stakeholders to implement data-analytical packages for clients in multiple domains;
- Perform data exploration in depth and design/implement novel algorithms to address data analytical challenges;
- Work closely with other platform teams to deliver integrated products or solutions
Skills And Qualifications:
- Excellent understanding of general machine learning techniques and popular models (linear regression, SVM, XGBoost/LightGBM, etc.), and basic deep-learning models.
- Experience with development tools like Python, NumPy/Pandas, Scikit-learn and one deep-learning framework (Tensorflow / Keras / PyTorch).
- Experience with data exploration tool and data visualization tool, such as matplotlib, Echarts, etc.
- Better with experience with SQL/NoSQL databases.
- Excellent written and verbal communication skills for coordinating across teams.