Quant Risk Analytics Analyst – Asia Markets

Polymer Capital Taiwan; Hong Kong; On-site; HKD 420,000 - 640,000; Full time

Benefits offered by this job

Paid Annual Leave

Medical Group Insurance

In-built Gym facility / Gym reimburse

DEI and Philanthropy Initiatives

Professional Learning & DevelopmentOp

Job summary

Polymer Capital Management in Hong Kong is seeking a data analytics/quant research professional to build and maintain quantitative tools for risk management and portfolio performance analysis. You will collaborate with portfolio managers to develop reports, test tools, and deploy them to production environments.

Ideal candidates have 2+ years in finance data analytics, strong programming in Python/R/C#, and familiarity with AWS, Docker, and modern data workflows.

Qualifications

• Bachelors or above in a quantitative field; advanced degree a plus.
• 2+ years in data analytics, quant research, or related finance roles.
• Strong programming skills in Python, R, and C#; familiarity with analytics.
• Experience with cloud and modern data pipelines is beneficial.

Responsibilities

• Research, build and maintain quantitative tools for risk management.
• Collaborate with portfolio managers to develop performance/risk reports.
• Test and deploy quantitative tools to Production environments.
• Handle ad-hoc data analysis tasks to support risk management.

Skills

Programming languages: Python, R, C#

Teamwork & communication

Independent thinking

Education

Bachelor’s or above in quantitative field

Advanced degree is a plus

Tools

AWS (Lambda, batch, ECS)

Terraform & Docker

Web development (JS, React, Angular, Vue)

ML frameworks: TensorFlow, PyTorch, XGBoost

Database development

Job description

Polymer Capital Management in Hong Kong is seeking a data analytics/quant research professional to build and maintain quantitative tools for risk management and portfolio performance analysis. You will collaborate with portfolio managers to develop reports, test tools, and deploy them to production environments.

Ideal candidates have 2+ years in finance data analytics, strong programming in Python/R/C#, and familiarity with AWS, Docker, and modern data workflows.