Job Description

Job Purpose

The primary purpose of this position is to analyze various data sets, gather and manage business requirements, design business solutions, and see said solutions to implementation. The incumbent will be required to lead and work with multiple teams to gain subject matters expertise, conduct feasibility studies, market analysis, define new processes as well as identify and implement process improvement opportunities. The incumbent will drive for solutions as they liaise and collaborate with various stakeholders for reference data teams such as our pricing, index, analytics and product management teams as well as our technology team to improve the quality, completeness, timeliness and breadth of multiple data sets.

The incumbent will serve as a subject matter expert for multiple data sets and present the Reference Data Operations (RDO) business needs to other stakeholders. They will have a deep understanding of complex processes, and business needs and present those concepts to others on the team. The incumbent must ensure that detailed gap analysis is conducted properly, identify opportunities and proposals for process improvements.

The fixed income and equities market consists of over two million active securities and the reference data provided by ICE Fixed Income & Data Services for said securities is used by our clients to make trading decisions, settle trades, make investment decisions, manage portfolios, analyze risk, create security master files, create client statements and conduct other back-office functions. Our reference data is also used by internal stakeholders such as the Evaluated Pricing, Index and Analytics groups said reference data plays an integral role in determining evaluated prices, determining whether or not a security should be added to or deleted from an index or indices, the weighted average of a security within an index and, performing a series of analytical calculations that are used both internally within ICE and externally by these stakeholder’s clientele.

Responsibilities

• Collaborate with vendors to design, develop, and implement AI solutions using Machine Learning and NLP technologies, leveraging understanding of LLM’s, SQL, databases, and testing frameworks.
• Utilize knowledge in programming languages such as SQL and Python, and data analysis tools to perform data analysis and recommend various solutions to improve data accuracy, timeliness, and completeness.
• Document well-organized, detailed, and concise business requirements by converting the results of data from interviews and conducting own analysis, particularly in the realm of artificial intelligence applications.
• Plan, organize, facilitate, and lead reviews of business requirements with users and developers to ensure accuracy, completeness and mutual understanding.
• Design and recommend various solution to improve data accuracy and completeness. Present alternative solutions and/or controls to stakeholders using analytics, charts, graphs, diagrams, and presentations. Make recommendation for best approach to harness efficiencies using automation.
• Evaluate efficiencies and improvements gained from recommended AI solutions, focusing on accuracy, timeliness, and overall completeness.
• Monitor project progress by tracking activity, resolving problems and publishing progress reports. Prepare production release notes and organize review sessions with RDO and other internal groups to ensure full understanding of release scope.
• Apply innovative problem-solving skills to create AI-driven workflows that elevate productivity.
• Write complete and concise test scripts for user acceptance testing. Plan, coordinate, and execute created tests cases in alignment with AI project requirements.
• Identify any potential data gaps resulting from the creation of new fields and/or rules. Work with related groups to confirm completion of data backfills required.
• Coordinate closely with the internal training team to ensure all training documentation is adjusted, and all training sessions are completed before the release rollout.
• Creates working relationships with Data Vendors to understand content and escalate issues.
• Exemplify mentorship by guiding and supporting junior members of the team, especially in their involvement with artificial intelligence endeavors.
  
  

Knowledge And Experience

• Bachelor’s degree or higher in Computer Science, Information Systems, or related technical field required or equivalent experience.
• Working experience on one or more large language models (LLMs).
• Experience working with APIs, data extraction using Python or similar language and SQL knowledge is required.
• Knowledge of various cloud computing platforms such as Amazon Web Services (AWS), or others.
• Familiarity with various Machine Learning Libraries and full understanding on their impact on AI solution is essential.
• Experience with Natural Language Processing (NLP) and Machine Learning models is a must, including experience with model operations tasks such as model deployment, monitoring, and performance evaluation.
• Familiarity with analytical tools such as R and data visualization tools such as Tableau or power BI is a plus.
• 5+ years of direct experience or equivalent
• Ability to work in a fast-paced, high-pressure, fluid environment.
• Ability to distill large amounts of information into specific takeaways.
• Excellent attention to detail and a high degree of demonstrated decision-making and problem-solving skills.
• Excellent written and oral communication skills, including the ability to communicate technical concepts to both technical and non-technical stakeholders.
• Knowledge of software development life cycle and experience with Agile methodologies is required.
  
  

Schedule

This role offers work from home flexibility of up to 2 days per week.