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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonRJavadata visualizationSQLAWSAzurefactor modelsstatistical modelingportfolio optimization

Soft Skills

leadershipcommunicationcollaborationmentoringinnovationproblem-solvingstakeholder managementfeedback facilitationtechnical translationstrategic planning

Certifications

Master’s degreePhD