Background

The Risk Business identifies, monitors, evaluates, and manages the firm’s financial and non-financial risks in support of the firm’s Risk Appetite Statement and the firm’s strategic plan. Operating in a fast paced and dynamic environment and utilizing the best in class risk tools and frameworks, Risk teams are analytically curious, have an aptitude to challenge, and an unwavering commitment to excellence.

Risk Engineering is a multidisciplinary group of quantitative experts who are the authoritative producers of independent risk & capital metrics for the firm. Risk Engineering is responsible for modelling, producing, reviewing, interpreting, explaining and communicating risk & capital metrics and analytics used to ensure the firm adheres to its Risk Appetite and maintains the appropriate amount of Risk Capital. Risk Engineering provides risk & capital metrics, analytics and insights to the Chief Risk Officer, senior management, regulators, and other firm stakeholders. 

Analytics & Reporting (A&R) is a group within Risk Engineering in the Risk Division of Goldman Sachs. The group ensures the firm’s senior leadership, investors and regulators have a complete view of the positional, market, and client activity drivers of the firm’s risk profile allowing them to take actionable and timely risk management decisions.

Role Responsibilities 

You will be part of the stress testing team responsible for:

• Delivering regular and reliable risk metrics, analytics and insights based on deep understanding of the firm’s businesses and its client activities. This involves enhancing and managing processes that quantify, review, explain and convey insight for risk and capital measures for a large, diverse set of financial products or activities across the firm, considering multiple types of risk including credit, market and operational risk.
• Supporting the development and execution of the capital planning quantification and stress testing programme, including regulatory stress testing, internal capital adequacy assessment process, recovery planning, or any ad-hoc stress testing performed for multiple legal entities across EMEA.
• Building robust, systematic and efficient workflows around the production of risk analytics to streamline and automate risk analysis.
• Developing and maintaining engaging approaches to share curated risk insights through interactive dashboard tools.
• Proactively liaising with groups such as Modelers/Strats, Engineers, Controllers, and Business to understand and explain observations in risk data.
• Communicating complex ideas with internal/external stakeholders such as risk managers, senior management, the firm’s regulators and auditors.

Opportunities 

In performing the job function, you will have the following opportunities:

• Work in a dynamic and highly creative teamwork and consensus-orientated environment.
• Exposure to industry leading market data, pricing and risk & capital models for all activities the firm engages in.
• Exposure to large volumes of data and the tools and techniques to interact with and determine meaningful interpretations of such data.
• Development of quantitative and programming skills.
• Development of economic, financial product and market knowledge.
• Engagement in critical risk management activities and opportunities to work with senior members of the firm and a wide variety of groups across all areas of the firm.

Qualifications, Skills & Aptitude 

The role is ideal for collaborative individuals who have sound technical skills, financial risk acumen, strong ethics, and attention to detail. Eligible candidates are preferred to have the following:

• Master's or Bachelor's degree in a quantitative discipline such as data science, mathematics, physics, econometrics, computer science or engineering.
• 3-5 years of experience in financial, regulatory, consulting or project management area.
• Good organisational and time management skills, with experience in leading projects involving multiple teams.
• Entrepreneurial, analytically creative, self-motivated and team-oriented.
• Excellent written and verbal communication skills.
• Experience with programming in Python and/or SQL for extract transform load (ETL) operations and data analysis will be beneficial.
• Experience in developing data visualization and business intelligence solutions using tools such as Tableau and PowerBI is beneficial.
• Working knowledge of the financial industry, markets and products and associated risks.
• Working knowledge of statistical modelling, such as regression, time series analysis, machine learning is beneficial.
   

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.