Data Scientist - AI & LLM for Investment Insights

GIC Private Limited; Singapore; Hybrid; SGD 180,000 - 240,000; Full time

Job summary

GIC seeks an AVP/VP Data Scientist in the Investment Insights Group in Singapore. You will join the data science and innovation team to build AI solutions that support enterprise-wide users, including investment and corporate functions.

The role requires formal quantitative training, strong LLM experience, and solid software engineering and statistical fundamentals, with 3+ years of ML engineering. You will work end-to-end from data gathering to model deployment.

Qualifications

• Formal training in a quantitative discipline (CS, physics, math, finance, engineering, etc.)
• LLM experience in industry settings is a must
• Strong in software engineering and best practices (e.g. code smell, single-responsibility principle)
• Strong in statistical fundamentals; experience with hypothesis testing and sampling
• Understanding of financial markets and multi-asset research is a plus
• Experience managing and accessing data in investment management research
• Ability to work end-to-end on research projects from data gathering to model implementation
• At least 3 years of hands-on engineering experience with data science or ML projects
• Good communication skills; able to explain results to stakeholders

Responsibilities

• Design and implement AI workflows to solve business problems
• Deploy AI solutions to production and iterate based on user feedback
• Conduct independent research from ideation to implementation
• Collaborate with stakeholders across investment and corporate functions

Skills

LLM experience

Software engineering

Statistical fundamentals

Communication skills

Data science

ML research

Financial markets

End-to-end research

3+ years ML engineering

Education

Formal training in quantitative discipline

Job description

GIC seeks an AVP/VP Data Scientist in the Investment Insights Group in Singapore. You will join the data science and innovation team to build AI solutions that support enterprise-wide users, including investment and corporate functions.

The role requires formal quantitative training, strong LLM experience, and solid software engineering and statistical fundamentals, with 3+ years of ML engineering. You will work end-to-end from data gathering to model deployment.