HCM - Dallas - Vice President, Data Analytics & Reporting - 9607793

Goldman Sachs•Dallas, TX

17h•Onsite

About The Position

The Vice President, Data Analytics & Reporting will be responsible for analyzing large and complex datasets to perform exploratory and advanced data analysis, applying established experimentation and analytical best practices. This role involves identifying, escalating, and resolving data, system, and algorithm performance issues. The position will design, develop, and implement Business & Artificial Intelligence applications, including defining and monitoring performance and risk indicators, and presenting analytical outcomes to stakeholders. Additionally, the role requires designing, developing, and maintaining scalable, automated, user-friendly systems, reports, and dashboards to support divisional business and analytical needs. Collaboration with cross-functional experts to share analytical approaches and reusable code, and leading stakeholder engagements to identify and implement low-code and automation opportunities are key aspects of this position. The Vice President will also manage and track analytics initiatives, and adapt analysis and development based on observations of data, process limitations, and implications of outcomes.

Requirements

Master’s degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, Management Information Systems, or related field and three (3) years of experience in job offered or in a related Data Analytics role OR Bachelor’s degree (U.S. foreign equivalent) in Computer Science, Computer Engineering, Management Information Systems, or related field and five (5) years of experience in job offered or in a related Data Analytics role.
Prior work experience must include three (3) years of experience (with a Master’s degree) OR five (5) years of experience (with a Bachelor’s degree) in applying data analytics techniques across multiple concurrent data initiatives, involving at least three (3) projects at a time, where the projects are in either a financial services context or a human capital management (HCM) context.
Prior work experience must include designing and delivering ETL (Extract, Transform, Load) development of database objects, SQL (Structured Query Language) queries and data analytic capabilities in cloud rational database platforms (such as Snowflake), traditional rational database platforms (such as Microsoft SQL Server) and centralized repository (such as Data Lake).
Prior work experience must include developing, maintaining and managing data driven dashboards and analytics using commercial data visualization tool kit, including experience with one of the following: Tableau, Power BI or Qlikview.
Prior work experience must include building and enhancing business intelligence applications, including automation, process optimization, data analysis, data visualizations, and report creations, using Alteryx or Power BI.
Prior work experience must include utilizing Python for data processing, web scraping, and generating reports.
Prior work experience must include designing, developing, and optimizing robust data models, including conceptual, logical, and physical, to support financial analytics and reporting, ensuring data integrity, scalability, and performance.

Responsibilities

Analyze large and complex datasets to perform exploratory and advanced data analysis.
Apply established experimentation and analytical best practices.
Identify, escalate, and resolve data, system, and algorithm performance issues.
Design, develop, and implement Business & Artificial Intelligence applications.
Define and monitor performance and risk indicators.
Present analytical outcomes to stakeholders.
Design, develop and maintain scalable, automated, user-friendly systems, reports, and dashboards.
Collaborate with cross-functional solution experts and advisors to share analytical approaches and reusable code.
Lead stakeholder engagements to identify and implement low-code and automation opportunities.
Manage and track analytics initiatives.
Extend and modify analysis and development based on observations of data, process limitations and implications of outcomes.