As an Equity Quantitative Investment Analyst (Analyst), you will support a growing and innovative Equity Portfolio Management team within Wealth Management’s Chief Investment Officer organization (Private Bank CIO Team). Reporting to senior members of the Quantitative Investments function within CIO Equities, you will help combine fundamental equity perspectives with quantitative and factor-based analytics to support investment decisions.

You will work closely with portfolio managers and fundamental analysts to support portfolio analytics, monitor the trade workflow, help produce risk and performance reporting, and contribute to quantitative research and portfolio construction workstreams across global equity and multi-asset portfolios.

• Portfolio & Risk Analytics Support: Assist with applying risk models (e.g., Axioma or similar) to monitor portfolio exposures, factor tilts, and risk concentrations; help prepare regular risk summaries and dashboards.
• Portfolio Construction Support: Help run portfolio analytics to support portfolio construction discussions (e.g., tracking active risk, sector/style exposures, constraints monitoring) and assist with basic performance and attribution reporting.
• Quantitative Research & Data Work: Support model development and research by cleaning/processing datasets, building repeatable analysis pipelines, and maintaining code and documentation. Contribute to factor research, backtests, and investment analytics under senior guidance.
• Collaboration & Communication: Prepare clear written summaries of analysis results for portfolio managers and investment stakeholders; explain methods and assumptions in a concise, practical way.
• Compliance & Controls: Maintain a consistent focus on controls, data quality, model governance, and risk/compliance requirements.

• 1+ years of experience in an investment, quantitative, risk, or analytics role (buy-side, sell-side, research, or relevant internship experience considered).
• Foundational understanding of equity markets, portfolio construction concepts, and investment risk (e.g., factor risk, tracking error, diversification).
• Working programming ability in Python (preferred) and/or R, including experience with data libraries such as Pandas and NumPy; ability to write clean, testable, well-documented analysis code.
• Basic knowledge of statistics/econometrics (e.g., regression, hypothesis testing) and comfort working with large datasets.
• Bachelor’s degree in a quantitative or analytical discipline (Finance, Mathematics, Engineering, Computer Science, Economics, or related).

• Exposure to equity risk models (Axioma or similar), factor models, and/or attribution frameworks through coursework or on-the-job experience.
• Familiarity with version control (e.g., Git), APIs, and automated reporting workflows.
• Interest in machine learning techniques as applied to investments (not required).
• Progress toward CFA (or interest in pursuing) is a plus.

• Strong analytical mindset, intellectual curiosity, and attention to detail.
• Clear, concise communication skills with the ability to translate quantitative results into practical takeaways.
• Strong teamwork and interpersonal skills; comfortable working in a fast-paced, collaborative environment.
• Good organizational skills with the ability to manage multiple priorities and deadlines.
• Genuine interest in financial markets and investing.