Data Science Artificial Intelligence Lead - Byers, United States - Intercontinental Exchange Holdings, Inc.

Description

Job Description:

Job Purpose

As an Artificial Intelligence Data Scientist Lead you will be working on Artificial Intelligence projects, your primary responsibility is to analyze complex data sets, design innovative business solutions, and oversee their implementation. You will be deeply involved in Machine Learning Operations and customization of vendor product to meet data quality standards. You will be working with multiple teams to gain subject matter expertise, conduct feasibility studies, market analysis, and identify and implement model changes.

Your role requires you to collaborate and liaise with various internal Technology and non technology team to ensure that the quality, completeness, timeliness, and breadth of various data sets are improved and trained models perform in optimal manner. 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 Lead Data Scientist, AI, 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 models architecture and oversee their production performance..

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 technology vendors to conceptualize, develop, and implement advanced Machine Learning (ML) solutions and Natural Language Processing (NLP) technologies. Leverage a robust understanding of Large Language Models (LLMs), SQL, databases, and testing frameworks in the design and deployment of ML operations.
• Utilize proficiency in programming languages like SQL and Python, along with data analysis tools, to conduct in-depth data analysis. Provide recommendations to enhance data accuracy, timeliness, and completeness through the application of ML techniques.
• 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.
• 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.
• Coordinate and collaborate effectively with the internal and external stakeholders, project team, including but not limited to end-users, product management, evaluations, index, portfolio analytics, quality assurance, project management, and development teams to develop complex models and tactical AI driven solutions.
• 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.
• 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.
• 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

• Bachelors 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 cloud computing platforms such as Amazon Web Services (AWS), or others; with a focus on their application in ML operations.
• Familiarity with 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.
• 7+ years of direct experience or equivalent in roles emphasizing ML operations, data analysis, and AI solution implementation.
• 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.