Data Scientist Intern — AI/ML in HK (Hybrid)

Intact; Hong Kong; Hybrid; HKD 134,000 - 201,000; Full time

Job summary

Intact, a leading Canadian insurer, invites applications for the Data Scientist Internship/Co-op in Hong Kong. Based at Science Park with a hybrid setup, you will contribute to cutting-edge AI and data science projects, collaborating with a global team to turn data into insights for customers.

You will work full-time for Winter 2027 or Summer 2027, leveraging Python and ML tools to tackle real-world problems in a supportive learning environment with leadership opportunities.

Qualifications

• Currently enrolled in a post-secondary degree in a quantitative discipline.
• Available to work full-time, 37.5 hours per week, for Winter 2027 (Jan–Apr) or Summer 2027 (May–Aug).
• Must be an active student during internship and/or returning to school after.
• Relevant experience in predictive modelling, ML and statistics is a plus.
• Unlimited curiosity and a passion to challenge the status quo.

Responsibilities

• Use ML and advanced statistics to build solutions for customer and business problems.
• Transform complex datasets into meaningful conclusions and recommendations.
• Grow with a diverse team of data science, software engineering, actuarial science, business and design experts.
• Collaborate with teams in HK & Canada to share knowledge and tools.
• Familiar with Python, NLP/LLM.

Skills

NLP/LLM

Curiosity

Education

Post-secondary degree in mathematics, science, engineering, statistics, AI, or computer science

Tools

Python

scikit-learn

xgboost

pytorch

tensorflow

LightGBM

pandas

Job description

Intact, a leading Canadian insurer, invites applications for the Data Scientist Internship/Co-op in Hong Kong. Based at Science Park with a hybrid setup, you will contribute to cutting-edge AI and data science projects, collaborating with a global team to turn data into insights for customers.

You will work full-time for Winter 2027 or Summer 2027, leveraging Python and ML tools to tackle real-world problems in a supportive learning environment with leadership opportunities.