AVP, Front Office Analytics & Risk Solutions

GIC Private Limited; Singapore; Hybrid; SGD 180,000 - 260,000; Full time

Job summary

GIC Private Limited seeks an AVP in the Portfolio Execution & Solutions Group to drive data-driven business solutions for the Front Office. You will work with researchers and portfolio managers to translate questions into models, backtest ideas, and validate results.

You will source specialised datasets, build scalable analytics, and lead AI-enabled workflows across Databricks and visualization tools, collaborating with technology, risk and operations teams.

Qualifications

• Bachelor's degree in quantitative discipline with strong finance/markets focus.
• 6–8 years of experience in asset management, financial services or related field.
• Strong programming in Python and SQL, with data engineering and visualization experience.

Responsibilities

• Engage senior Front Office stakeholders across PESG to define and refine business solutions needs.
• Translate investment questions into quantitative models, supporting design, backtesting and validation.
• Act as the point person for demand management and roadmap planning within PESG.
• Source and structure fit-for-purpose datasets enabling scalable research and analytics.
• Oversee timely delivery of analytics using platforms, AI tools and data pipelines.
• Apply AI to accelerate data prep, model development and research workflows.
• Collaborate with technology, operations and risk teams to meet Front Office needs.
• Share learnings to uplift service levels and deepen team knowledge.

Skills

Python

SQL

Excel

Data visualization

Education

Bachelor's degree in quantitative discipline

CFA/FRM preferred

Tools

Tableau

Databricks

Job description

GIC Private Limited seeks an AVP in the Portfolio Execution & Solutions Group to drive data-driven business solutions for the Front Office. You will work with researchers and portfolio managers to translate questions into models, backtest ideas, and validate results.

You will source specialised datasets, build scalable analytics, and lead AI-enabled workflows across Databricks and visualization tools, collaborating with technology, risk and operations teams.