Conduct technology scans and proof-of-concepts, preprocess data, engineer features, build machine learning models, and present systems to management and users. Potential projects include statistics, machine learning, data visualization, human language technologies, and graph analytics. Interns work closely with mentors to meet project requirements.
Duration: 2 - 4 Months
Internship Type: Undergraduate, Pre-University
As a Data Scientist, you will have to understand the project objective and requirements, conduct technology scan and proof-of-concept (if required). You will work closely with a mentor to deliver a system meeting the project requirements.
Broad Deliverables
- Conduct technology scan and proof-of-concept (if required).
- Perform data pre-processing and feature engineering, build and develop machine learning models.
- Present the system to management and users.
Possible Projects*
- Statistics and machine learning
- Data visualization
- Human language technologies
- Graph algorithms/analytics
Prerequisites/Skills Required
- Prior knowledge in data mining or machine learning techniques (e.g. classification, anomaly detection and recommendation systems)
- Proficient in programming language such as Python (i.e. familiar with Python-based machine learning libraries such as scikit-learn, numpy/scipy and pandas)
In your application, please submit the following documents in a single PDF file for 'Resume/CV':
1. Resume/CV
2. All Education Certificates to-date (from secondary to tertiary education)
- GCE 'O'/'N' Levels, NITEC
- Prelim/GCE 'A' Levels, IB/Diploma
- Latest university transcript from Year 1 (for current undergraduates)
3. Student Status Letter/Degree Audit (for current undergraduates)
Centre for Strategic Infocomm Technologies Singapore, Singapore, SGP Office
Singapore, Singapore
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The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
