Vice President, Internal Audit, Data Analytics

Goldman Sachs

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Quick summary

Work type: On-site
Location: New York, NY
Salary: $100,000–$250,000 / yr
Posted: 104 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $166k

This role $175k

$82k $268k

below market most similar roles pay here above market

This role pays more than 58% of similar roles. Most pay $140,412–$192,287 — the blue band above. At the midpoint, this role pays about $175k versus about $166k for comparable roles.

Based on 240 similar postings.

Employer

About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 71 open roles on FindRole.

Listed pay typically runs $140,000–$250,000 across 34 roles with salary data.

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At a glance

TL;DR · Vice President, Internal Audit, Data Analytics

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The Internal Audit, Data Analytics, Vice President, New York joins the Embed Data Analytics team to provide independent assurance on the firm’s internal control structure. This role involves building innovative, reusable analytical tools and data-driven solutions to improve audit testing efficiency and identify control gaps. You will perform data modeling, engineering, and governance while executing ETL processes for structured and unstructured data. Key responsibilities include writing code in Python, Java, or C++, and developing production-ready tools using Tableau, Spotfire, or QlikView. The position requires expertise in RDBMS/SQL, statistics, and machine learning algorithms like Random Forest and Clustering. You will partner with audit teams to facilitate strategic data sourcing, ensure data integrity through Data Blessing, and address complex problems within the firm's risk management and governance framework.

Skills

Python Java C++ SQL R SAS SPSS Tableau Spotfire QlikView ETL Data Engineering Data Modeling Data Governance Machine Learning NLP Time Series Analysis Regression Data Science RDBMS

What you'll do

Perform data modeling, data engineering, data governance, and maintenance of entitlements.
Manage project requirements to provide insights on sample selection, control gap identification, and data integrity.
Build production-ready analytical tools to automate repeatable processes using Tableau, Spotfire, or QlikView.
Execute ETL processes to extract, transform, and upload structured and unstructured data.
Write data analysis code using programming languages such as Python, Java, or Slang.
Identify areas for process standardization and implement automation techniques for audit processes.
Partner with audit teams to identify business risks and facilitate strategic data sourcing.

What we're looking for

Minimum of a bachelor’s degree in computer science, Math, or Statistics.
8+ years of experience in the field.
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.
Experience with advanced data analytics tools and techniques (preferred).
Familiarity with text analytics and NLP using Python (preferred).
Familiarity with machine learning algorithms and supervised/unsupervised learning (preferred).
Experience with analytical/statistical programs such as SAS, SPSS, and R (preferred).
Experience with visualization tools like Tableau, Spotfire, or QlikView (preferred).

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