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

The Goldman Sachs Group

New York (NY)

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

The Goldman Sachs Group's Internal Audit team in New York seeks a seasoned Data Scientist to join the Embed Data Analytics group. You will build data-driven tools to support audit testing, collaborate with audit teams, and translate complex data into actionable insights that strengthen the firm's control environment.

Requirements include 8+ years in data science, strong SQL, Python, Java, ETL, and visualization tools.

Qualifications

  • 8+ years of experience 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 and their application to data.
  • Strong communication skills and ability to work in a team.
  • Proven collaboration within a Data Science team and initiative to improve performance.

Responsibilities

  • Perform database-related activities – Data Modeling, Data Engineering, Data Governance, and maintenance of Entitlements.
  • Manage requirements tailored to each audit project and provide results for audit insights (sample selection, data integrity, etc.).
  • Build production-ready analytical tools to automate processes using Tableau, Spotfire or QlikView.
  • Execute data analysis activities including ETL procedures and data extraction/transformation/uploading.
  • Provide summarized technical narratives describing the integrity of automated controls.
  • Write data analysis code (Python, Java, or C++).
  • Identify areas for process standardization and automate audit/applications tools.
  • Support Embed DA data strategy with risk assessment, audit planning and reusable tools.

Skills

SQL
Python
Java
C++
ETL
Data Blessing
Statistics
Communication
Tableau
SAS/SPSS/R

Education

Bachelor's in Computer Science / Math / Statistics

Tools

Tableau
Spotfire
QlikView
SAS
SPSS
R

Job description

What We Do

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
  • Raise awareness of control risk
  • Assesses the firm's control culture and conduct risks; and
  • 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.

Who We Look For

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 firm's businesses and functions, including securities, investment banking, consumer and investment management, risk management, finance, cyber-security and technology risk, and engineering.

Data Analytics

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 designated 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
  • 8+ years of experience with a minimum of a 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 their 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 the Internal Audit Division.
  • Driven and motivated and constantly taking initiative to improve performance.
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 pattern 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 the department.
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