Job Description

Job Purpose

As a Technical Project lead working on Artificial Intelligence projects, your primary responsibility is to analyze complex data sets, gather and manage business requirements, design innovative business solutions, and oversee their implementation. You will be working with multiple teams to gain subject matter expertise, conduct feasibility studies, market analysis, and identify and implement process improvement opportunities.

Your role requires you to collaborate and liaise with various business reference data teams such as Evaluations, Index, multiple Product and Project Management, as well as Technology to ensure that the quality, completeness, timeliness, and breadth of various data sets are improved. You will leverage your expertise in Artificial Intelligence to support the development of solutions that leverage advanced technologies to automate business processes, improve efficiency, and drive business outcomes.

As a Tech-Project Lead, you must have the ability to work with subject matter experts from various teams, understand complex processes and business needs, and present those concepts to others. You will conduct detailed gap analysis to identify opportunities and propose various viable solutions. You will also be required to gather and maintain a comprehensive library of detailed business requirements and oversee their production, while adhering to a set release cycle to ensure successful implementation.

Your work will be critical to the success of ICE Data Services in providing reference data that 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. You will leverage your expertise in Artificial Intelligence to help develop innovative solutions that drive automation and efficiency in the management of these complex data sets.

Responsibilities

• Collaborate with vendors to design, develop, and implement AI solutions using Machine Learning and Natural Language Processing (NLP) technologies, with a focus on extracting content from unstructured documents.
• Utilize expertise in programming languages such as SQL and Python, and data analysis tools such as R to perform data analysis and recommend various solutions to improve data accuracy, timeliness, and completeness.
• Working experience on one or more large language models (LLMs).
• Create data visualizations utilizing tools such as Tableau or power BI to present and recommend alternative solutions as well as drive data-driven decision-making.
• Possess deep knowledge of APIs and be able to leverage this expertise to communicate with various data sources and vendors.
• Conduct feasibility studies to determine the technical and economic feasibility of the proposed solution.
• Understand and document well-organized, detailed, and concise business requirements by converting the results of data from interviews and conducting own analysis.
• Identify opportunities in current processes, conduct GAP analysis to quantify issues, and recommend alternative solutions that will optimize process and/or improve the completeness, timeliness, and quality of the data set.
• Plan, organize, facilitate, and lead reviews of business requirements with users and developers to ensure accuracy, completeness, and mutual understanding.
• Coordinate and collaborate effectively with the project team, including but not limited to end-users, product management, evaluations, index, portfolio analytics, quality assurance, project management, and development teams to mitigate and assess project risks, eliminate ambiguities, and meet project deadlines.
• Examine current business functions and system capabilities. Identify trends and causation of inaccurate and/or incomplete data sets by conducting in-depth root cause analysis.
• Determine efficiencies, accuracy, timeliness, completeness gained from recommended solutions.
• Monitor project progress by tracking activity, resolving problems, and publishing progress reports. Prepare production release notes and organize review sessions with internal teams.
• Apply problem-solving skills to create innovative workflow resulting in increased productivity.
• Write complete and concise test scripts for user acceptance testing. Plan, coordinate, and execute created test cases.
• 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 after a production release.
• Train team members on the use of AI tools and participate in the initial operational set-up for the deployment of new AI-enabled systems.
• Coordinate closely with the internal training team to ensure all training documentation is adjusted, and all training sessions are completed before the release rollout.
  
  

Knowledge And Experience

• Bachelor’s degree or higher in Computer Science, Information Systems, or related technical field required or equivalent experience.
• 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 as a technical business analyst.
• 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.