Internal Audit- Data Analytics - Vice President

Internal Audits mission is to independently assess the firms internal control structure, including the firms 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 managements control measures.
In doing so, Internal Audit:
Communicates and reports on the effectiveness of the firms governance, risk management and controls that mitigate current and evolving risk
Raise awareness of control risk
Assesses the firms control culture and conduct risks
Monitors managements implementation of control measures
Goldman Sachs Internal Audit comprises individuals from diverse backgrounds including chartered accountants, developers, risk management professionals, cybersecurity professionals, and data scientists. We are organized into global teams comprising business and technology auditors to cover all the firms businesses and functions, including securities, investment banking, consumer and investment management, risk management, finance, cyber-security and technology risk, and engineering.
Who We Look For
Goldman Sachs Internal Auditors demonstrate a strong risk, control and analytical mindset, exercise professional skepticism and challenge status quo on risks and control measures effectively with management. We look for individuals who enjoy learning about audit, businesses and processes, have innovative and creative mindset in adapting analytical techniques to enhance audit function, develop teamwork and build relationships and are able to evolve and thrive in a fast-paced global environment
Embed - Data Analytics
In Internal Audit, we ensure that Goldman Sachs maintains effective controls by assessing the reliability of financial reports, monitoring the firms compliance with laws and regulations, and advising management on developing smart control solutions. 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 firms 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 firms 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 firms control environment.
Responsibilities
Perform Databases 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 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.
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 where for process standardization and implement automation techniques 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
7+ years of experience with a minimum of Bachelors in Computer Science, Math, or Statistics
Strong experience in RDBMS/ SQL and Data Warehousing.
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.
Preferred Qualifications
Experience with advanced data analytics tools and techniques
Familiarity with text analytics and NLP using python
Familiarity with machine learning algorithms and exposure to supervised and unsupervised learning - Linear/Logistic Regression, SVM, Random Forest and Boosting, Clustering and Patterns Recognition techniques
Experience with analytical/ statistical programs such as SAS, SPSS, and R
Experience with visualization tools (Spotfire, Qlikview or Tableau) 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