Investment Risk Analyst: Data-Driven Risk & Automation

Randstad Hong Kong Limited; Hong Kong; On-site; HKD 420,000 - 650,000; Full time

Job summary

Randstad Hong Kong Limited is a boutique investment management firm focusing on hedge fund allocation across Asia and globally. The Risk Monitoring & Reporting role requires monitoring risk exposures daily to monthly, generating comprehensive risk reports, and collaborating with portfolio teams to resolve data issues.

You will drive process automation with Python, manage large datasets, and build dashboards for senior management, while improving risk infrastructure and controls.

Qualifications

• Bachelor’s degree in finance or quantitative field is required.
• 1–4 years in investment risk, portfolio analytics, or asset management operations.
• Proficient in Python for data manipulation and automation.
• Strong Excel skills; VBA is a plus; SQL experience is preferred.

Responsibilities

• Monitor daily, weekly, and monthly risk exposures across regional and global portfolios.
• Generate and maintain risk reports tracking tracking error, VaR, stress tests, and beta.
• Collaborate with global offices and portfolio teams to resolve data issues and align reporting standards.
• Document business requirements and strengthen internal controls over risk reporting.
• Build and optimize dashboards for senior management using data visualization tools.

Skills

Investment Risk

Market Risk

Data Visualization

Python

Excel

SQL

Data Management

Education

Bachelor’s degree in Finance, Financial Engineering, Economics, Mathematics, Computer Science, or related quantitative field

Tools

Bloomberg

FactSet

Aladdin

Barra

RiskMetrics

Job description

Randstad Hong Kong Limited is a boutique investment management firm focusing on hedge fund allocation across Asia and globally. The Risk Monitoring & Reporting role requires monitoring risk exposures daily to monthly, generating comprehensive risk reports, and collaborating with portfolio teams to resolve data issues.

You will drive process automation with Python, manage large datasets, and build dashboards for senior management, while improving risk infrastructure and controls.