Team Lead, Investment Risk Technology

Role Overview

• Lead the design, development, and implementation of the Investment Risk Platform, ensuring scalability, reliability, and alignment with business goals.
• Drive innovation by integrating advanced analytics, factor models, and machine learning techniques into the platform.
• Oversee and contribute towards the end-to-end lifecycle of platform development, including requirements gathering, architecture design, coding, testing, deployment, and ongoing maintenance.
• Develop and implement robust factor models to assess portfolio risk exposures across multiple asset classes.
• Collaborate with investment teams to identify key risk drivers and translate them into actionable metrics within the platform.
• Ensure the platform provides accurate reporting and analytics on risk metrics such as volatility, tracking error, Value-at-Risk (VaR), stress testing results, and attribution analysis.
• Act as a bridge between technical teams (engineering, data science, analytics) and investment teams (portfolio managers, analysts) to ensure alignment on objectives and priorities.
• Communicate complex technical concepts to non-technical stakeholders in an accessible manner while understanding investment professionals’ needs deeply.
• Facilitate regular meetings with stakeholders to gather feedback and refine platform features.
• Build and mentor a high-performing team of developers and analysts dedicated to the Investment Risk Platform.
• Stay abreast of industry trends in risk management technologies and methodologies to ensure our platform remains best-in-class.
• Collaborate with senior leadership to define long-term strategies for enhancing risk management capabilities across the organization.

Requirements

• Demonstrated experience in building investment risk platforms or similar systems within financial services organizations.
• Strong programming skills in languages such as Python, R, or Java; familiarity with data visualization tools like Tableau or Power BI is a plus.
• Proficiency in working with large-scale data systems (e.g., SQL databases, cloud platforms like AWS or Azure).
• Expertise in quantitative finance concepts including factor models (e.g., Fama-French), risk exposures (e.g., beta, alpha), portfolio optimization techniques, and statistical modeling.
• Deep understanding of financial markets across asset classes such as equities, fixed income, derivatives, etc.
• Familiarity with regulatory requirements related to investment risk management.
• Advanced degree (Master’s or PhD) in Finance, Economics, Computer Science, Data Science, or related fields is preferred.
• Experience working with portfolio management systems such as Bloomberg PORT or BlackRock Aladdin is highly desirable.
• Knowledge of machine learning applications in financial risk modeling is a strong plus.

Tech Stack

• AWS
• Azure
• Cloud
• Java
• Python
• SQL
• Tableau

Benefits

• comprehensive health care coverage and emotional well-being support
• market-leading retirement
• generous paid time off and parental leave
• charitable giving employee match program
• educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career