Internal Audit-Data Analytics, Data Engineer -New York-Vice President

Goldman Sachs•New York, NY

11d•Onsite

About The Position

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. 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. 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 firm’s control environment.

Requirements

8+ years of experience with a minimum of bachelor’s in computer science, Math, or Statistics
Strong experience in RDBMS/ SQL
Exposure to ETL Processes, Data Engineering and Data Governance
Experience in implementing Data Blessing/Data Quality measures and entitlement models
Proficiency in programming languages, such as Python, Java, or C++
Knowledge of basic statistics, including descriptive statistics, data distribution models, Time Series Analysis, correlation, and regression, and its application to data
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
Strong contributing member of Data Science team and help build analytical capabilities for Internal Audit Division
Driven and motivated and constantly taking initiative to improve performance

Nice To Haves

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 (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

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