AI/ML Engineer - Lead Analyst

The Digital Solutions and Innovation (DSI) function works with members of Internal Audit (IA) to identify automation opportunities and develop solutions and capabilities to support the development of audit analytics. A key aspect of DSI’s strategy is to develop and deploy augmented intelligence (AI) and machine learning (ML) capabilities that are integrated with applications used by IA teams. The overarching objectives of these capabilities is to provide “in the moment” guidance to auditors, glean broader and deeper insights, enable efficiencies, and promote better quality and consistency. Role Overview: The AI/ML Engineer - Lead Analyst is a critical role with the objective of exploring, developing, testing, deploying, enhancing, and maintaining machine learning and artificial intelligence capabilities integrated with Internal Audit’s management systems. A broad understanding of AI/ML concepts and techniques, agile methodologies, cloud computing, intelligent chatbots, and related aspects is essential for the role. Additionally, a key aspect of this role involves the design and refinement of prompts to effectively communicate with generative AI models and to guide them, optimizing their output for a variety of technical applications and producing high-quality and contextually relevant content. The role will entail collaborating with DSI, audit teams, external third parties and technology teams on ML use case ideation and prioritization, developing plans and timelines for implementation, thorough testing, deployment in a systemic way, maintenance to keep the capabilities up to date and relevant, and support in the onboarding of new technology for DSI. The role will also involve collaborating with DSI team members and audit teams on new use case ideation, exploration, and eventual implementation. Another success factor for the role will be documentation of model performance and other metrics and communication/presentation of results to pertinent audiences, including senior leadership. Along with a strong technical foundation, a creative, imaginative, forward-looking attitude and mindset is needed to continue to exert a positive impact on DSI and Internal Audit. Furthermore, a total quality assurance orientation is indispensable in all activities and outputs. Key Responsibilities: Design, test, deploy and maintain machine learning use cases leveraging IBM Watson SaaS environment and toolset, and integrate with the audit management systems Enhance existing AI/ML capabilities through ideation, exploration, testing, prioritization, and implementation Design, test, and refine prompts to elicit the desired outputs from generative AI models, ensuring clarity, accuracy, effectiveness, and contextual relevance. Perform analytics on AI/ML capabilities usage to understand trends, patterns, and pain points and implement a sustainable feedback loop to ensure positive, continually improving user experiences. Explain the analysis of results in a methodical, analytical, visually-appealing manner Collaborate with Innovation, technology, vendor, and information security teams on updates, enhancements, releases, and other procedural requirements Assess current capabilities and chart a path for continuous improvement of the AI/ML capabilities value and impact Prepare, manage, and maintain model risk management (MRM) documentation on model performance and accuracy Engage with MRM team on adhering to and fulfilling requirements for MRM process Engage with relevant stakeholders on use case ideation, planning, development, and deployment Apply strong project management skills to develop project plans, timelines, milestones, and demonstrate progress toward objectives Utilize excellent communication skills to ideate, educate, and present internally, often at senior levels (across functions); expected to communicate with external parties Help shape the direction of machine learning and artificial intelligence capabilities in DSI Apply a strong understanding of business processes, risks and controls to identify opportunities to enhance audit efficiencies and effectiveness through the development and delivery of automated processes Drive tool innovations based on stakeholder needs, including adoption of new technologies and techniques Qualifications: 5+ years’ experience in AI, machine learning, and model development and deployment Extensive experience in machine learning use case design, testing and deployment in IBM SaaS/Watson environment Firm understanding of IBM cloud environment and its services Demonstrable experience with IBM OpenPages platform, coupled with implementation and integration of machine learning algorithms using Watson capabilities Demonstrable experience in working with Generative AI models, with a deep understanding of their capabilities, prompting strategies, model performance, and inherent limitations. Extensive experience testing and using APIs Strong statistical foundation, with in-depth knowledge of supervised, unsupervised, and semi-supervised machine learning models, with a particular focus on NLP/NLU Solid understanding of data structures and data models Understanding of conversational AI concepts, including intents, entities, dialogs trees, actions, journeys, and experiences Experience in application development and UI and UX considerations Experience in analytics, reporting, and visualization for the analysis and presentation of results. Cognos analytics experience is a plus Possess an innovative, forward-looking, and imaginative mindset to continually reach for new horizons in audit innovation Demonstrable experience working with stakeholders and exceeding their expectations Take responsibility and accountability for planning, execution, and delivery Positive attitude and a change-driven and change-oriented outlook Adept at developing new ideas and improving current processes Consider broad implications of decisions to different functions and units Ability to thrive in a fast-paced, results-oriented environment Excellent communication and interpersonal skills, with ability to develop strong working relationships and foster team collaboration Possess excellent writing skills to deliver clear and concise messages, able to articulate complex concepts Strong Presentation skills – comfortable with public speaking across various forums and be able to effectively and logically communicate when ideas are being challenged in an open forum Familiarity with Financial Services industry and/or auditing a plus Knowledge and Skills: Analytics, AI, machine learning, natural language processing (NLP), natural language understanding (NLU), large language models (LLMs) Generative AI prompt engineering and tuning Design of AI/ML model performance metrics and optimization SaaS environments, cloud computing IBM Watson, Watsonx.ai, Watson Assistant, OpenPages, Cognos Agile and waterfall project management methodologies; JIRA a plus Intermediate to Advanced level Python coding Advanced SQL MicroStrategy, Power BI, Tableau, or other visualization software Intents, entities, dialogs, actions, and related chat bot concepts are a plus Education: Bachelor’s degree in Data Science, Computer Science, MIS, or related discipline. CISA, PMP, Agile/Scrum, Cloud Computing, or related certifications are a plus. Master’s degree is a plus. #J-18808-Ljbffr Citigroup