Data Science Internship: AI, ML & Fraud Analytics

Shift Technology; Singapore; On-site; SGD 27,000 - 36,000; Full time

Benefits offered by this job

Flexible remote/hybrid

Competitive salary + variable bonus

Learning & development

Generous PTO

MAD Days

Job summary

Shift Technology in Singapore is offering a six-month Data Science internship on-site starting January or February 2027. You will join the Data Science team working on fraud detection, ML, NLP, and data pipelines, with exposure to production-quality code.

We welcome recent graduates or final-year students in Math, Stats, Software Engineering, Data Science or ML who have OOP experience (C# a plus) and can clearly explain technical findings to non-technical colleagues.

Qualifications

• You are a recent graduate or in the final year of a bachelor’s or master’s program in Mathematics, Statistics, Software Engineering, Data Science or Machine Learning.
• You have experience in object-oriented programming (OOP) such as internships or projects; familiarity with C# is a plus.
• Solid understanding of statistics and machine learning concepts.
• Ability to articulate findings to non-technical audiences.

Responsibilities

• Setting up and deploying data processing pipelines, such as data reception (batch or real-time), data cleaning, information extraction, and calibration of fraud detection models.
• Collaborating with clients to understand their needs and incorporating feedback to enhance our solutions.
• Conducting R&D to drive product innovation (machine learning, NLP, image analysis, trend analysis, chatbots, etc.).

Skills

OOP experience

C#

Communication skills

Education

Bachelor's or Master's in Mathematics, Statistics, Software Engineering, Data Science or Machine Learning

Job description

Shift Technology in Singapore is offering a six-month Data Science internship on-site starting January or February 2027. You will join the Data Science team working on fraud detection, ML, NLP, and data pipelines, with exposure to production-quality code.

We welcome recent graduates or final-year students in Math, Stats, Software Engineering, Data Science or ML who have OOP experience (C# a plus) and can clearly explain technical findings to non-technical colleagues.