Data Analytics

Internal Audit’s mission is to independently assess the firm’s internal control structure, including the firm’s governance processes and controls, risk management, capital and anti-financial crime framework. In addition, it is also to raise awareness of control risk and monitor the implementation of management’s control measures.

In doing so, Internal Audit:

• Communicates and reports on the effectiveness of the firm’s governance, risk management and controls that mitigate current and evolving risk
• Raises awareness of control risk
• Assesses the firm’s control culture and conduct risks
• Monitors management’s implementation of control measures

Goldman Sachs Internal Audit is organized into global teams comprising of business and technology auditors that cover all the firm’s businesses and functions - securities, investment banking, consumer and investment management, risk management, finance, cyber-security and technology risk, and engineering.

In Internal Audit, we ensure that Goldman Sachs maintains effective controls by assessing the reliability of financial reports, monitoring the firm’s compliance with laws and regulations, and advising management on developing smart control solutions. The Embed Data Analytics team leverages its programming and analytical capabilities to build innovative data-driven solutions. The team works closely with auditors to understand their pain points and develop data-centric solutions to address the same.

Your Impact:

As part of the third line of defense, you will be involved in independently assessing the firm’s overall control environment and its effectiveness as it relates to current and emerging risks and communicating the results to local/global management. In doing so, you will be supporting the provision of independent, objective and timely assurance around the firm’s internal control structure, thereby supporting the Audit Committee, Board of Directors and Risk Committee in fulfilling their oversight responsibilities. We are looking for a strong data scientist, passionate about using data to challenge the norm, to join our Embed Data Analytics team. The candidate will work closely with the audit teams to build innovative and reusable analytical tools that will help make audit testing more efficient and provide meaningful insights into the firm’s control environment.

Responsibilities:

• Perform Database related activities – Data Modeling, Data Engineering, Data Governance and maintenance of Entitlements
• Obtain/Manage requirements that are tailored to each audit project and provide the results that can be used to provide insight to auditors in terms of sample selection, control gap identification, completeness of data sources, and data integrity (i.e., Data Blessing)
• Build production ready analytical tools to automate repeatable and reusable processes within IA using reporting tools such as Tableau, Spotfire or Qlikview
• Execute elected data analysis activities. Such activities may be defined as procedural or programmatic tasks related to the analysis, extraction, transformation, and uploading of data (structured and unstructured) (i.e., ETL processes).
• Perform Data analysis activities that may also be supplemented by summarized technical narratives describing the integrity of specific automated controls.
• Write data analysis code (e.g. Python, Java, or Slang)
• Identify areas for process standardization and implement automation techniques in applications used for audit process and Data Analytics
• Execute on Embed DA - Data strategy developed by IA management within the context of audit responsibilities, such as risk assessment, audit planning, creation of reusable tools and providing innovative solutions to complex problems
• Partner with audit teams to help identify risks associated with businesses and facilitate strategic data sourcing and develop innovative solutions to increase efficiency and effectiveness of audit testing
• Build and manage relationships and communications with Audit team members

Basic Qualifications:

• 3+ years of experience with a minimum of bachelor’s in computer science, Math, or Statistics
• Strong experience in RDBMS/ SQL
• Exposure to ETL Processes and Data Engineering
• Experience in implementing Data Quality measures and entitlement models
• Familiarity in programming languages such as Python
• Strong team player with excellent communication skills (written and oral). Ability to communicate what is relevant and important in a clear and concise manner and ability to handle multiple tasks
• Self-driven and motivated to take up initiatives to improve our processes

Preferred Qualifications:

• Experience with data analytics tools and techniques
• Experience with analytical/statistical programs such as SAS, SPSS, and R
• Experience with visualization tools (Tableau, Spotfire or QlikView) is a plus
• Creativity/Innovation, i.e., ability to create new ways to improve current processes and develop practical solutions that add value to department

About Goldman Sachs:

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We’re committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.

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.