Global Banking & Markets Operations-FIS Sales & Trading Services-Dallas-Associate

Goldman Sachs•Dallas, TX

About The Position

Goldman Sachs is a leading global financial services firm. Operations is central to the firm, enabling business flow by supporting banking, sales and trading, and asset management capabilities globally. The Operations business also provides essential risk management and control. This role is within Fixed Income Securities, supporting institutional desks with trade booking, confirmation, pre-matching, and fails management. The team also handles exception detection, research, resolution, and escalation of position and cash differences. The specific role focuses on Business Intelligence (BI) and Artificial Intelligence (AI) within the fixed income middle office team, aiming to enhance automation, reporting, and data analysis to improve efficiency.

Requirements

Bachelor’s degree or equivalent in Science, Technology, Engineering or Mathematics / other relevant experience in financial companies in a role with a focus on data.
Relevant experience in an analytical, operations or similar role with a proven track record for managing multiple processes, functions and driving change.
Experience in using business intelligence platforms (i.e. Alteryx, Tableau, Qlikview, Power BI, Server/Database maintenance, Aqua Data Studio).
Developer skills including but not limited to: SQL, Python, R, Machine Learning and AI applications, Jira, Confluence.
Self motivated with the ability to act as an individual contributor and amongst the broader global BI team.
Familiarity with data and analytical tools such as SQL, Python, R, Jira, and Confluence in addition to problem solving, process improvement, and adoption of AI tooling.
Ability to develop cooperative and constructive working relationships with a strong sense of functional curiosity and passion for understanding the needs of the business.

Nice To Haves

Operations/middle office experience

Responsibilities

Work with a wide range of stakeholders primarily across Operations and Engineering, demonstrating both verbal and written communication skills.
Drive conversations with senior stakeholders to clearly articulate needs of the business, identify root cause issues, and influence the problem solving process.
Leverage partnerships to ensure low code is provisioned in the context of the firm’s wider technology architecture strategy.
Advise on evolving solution applications while keeping a view of full low code toolkit through solution design forums.
Develop automated solutions which connect upstream data sources to end user platforms.
Utilize any available established APIs and nurture our partnership with Engineering to create new APIs where required.
Provide end users with data analytics and risk reporting, giving AWM stakeholders the opportunity to make data driven decisions.
Identify manual processes which are inefficient and prone to errors, focusing on risk mitigation and resource capacity.
Drive conversations and lead the business intelligence programs for a variety of stakeholders, each with their own unique datasets and business needs.
Coach and mentor business unit embedded specialists, ensuring that embedded specialists are meeting the strict governance standards.
Contribute to ever changing Business Intelligence and Artificial Intelligence risk and governance framework.
Apply AI tools and prompt engineering techniques to solve operational problems, improve workflows, and support scalable business solutions across Operations.
Partner with Operations stakeholders to identify business challenges, define use cases, and translate operational needs into practical AI-enabled solutions.
Design, test, and refine prompts and AI-assisted workflows to improve process efficiency, reduce manual effort, and mitigate operational risk.
Evaluate where AI capabilities can enhance business intelligence, reporting, data interpretation, and end-user decision making.
Work with Engineering and technology partners to ensure AI-enabled and low-code solutions align with the firm’s broader technology architecture and governance standards.
Support the responsible use of AI by contributing to evolving business intelligence and artificial intelligence risk and governance frameworks.