Internal Audit - Vice President, Embedded Analytics Data Engineer - Dallas, TX

Internal Audit

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. Our group has unique insight on the financial industry and its products and operations. We're looking for detail-oriented team players who have an interest in financial markets and want to gain insight into the firm's operations and control processes.

Your Impact

We are looking for a strong data scientist, passionate about using data to challenge the norm, to join our Embedded 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

• 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

• 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

• 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