Business Analytics Lead Analyst, VP - Product & Portfolio Analytics | USCC Partnership Cards

As an Applications Development Technology Lead Analyst at Citi, you will play a crucial role in establishing and implementing new or revised application systems and programs in coordination with the Technology team. Your primary responsibility will be to lead applications systems analysis and programming activities. Here is a detailed overview of what will be expected from you: Key Responsibilities: - Lead the design and execution of complex data analysis and AI/ML initiatives across large, structured, and unstructured datasets. - Develop and deploy predictive, classification, clustering, and forecasting models to support business strategy and risk management. - Partner with business stakeholders to translate requirements into analytical and machine learning solutions. - Design and implement feature engineering pipelines and model evaluation frameworks. - Collaborate with Data Engineering teams to ensure scalable data pipelines and ML-ready datasets. - Operationalize machine learning models through production deployment and monitoring (MLOps practices). - Analyze trends, anomalies, and behavioral patterns using statistical and machine learning techniques. - Ensure model governance, explainability, fairness, and compliance with regulatory requirements. - Automate analytics workflows and implement scalable AI-driven solutions. - Present analytical findings and model insights to senior leadership and cross-functional teams. - Mentor junior analysts and data scientists on advanced analytics and ML best practices. - Drive continuous improvement in analytical methodologies, model performance, and reporting standards. - Influence strategic decisions through data science and AI-powered insights. - Manage multiple priorities in a fast-paced, highly regulated environment. Qualifications Required: - 8-12 years of relevant experience in Data Analytics, Data Science, or Advanced Analytics roles. - Extensive experience in system analysis and programming of software applications. - Foundation in Machine Learning and Deep Learning, including proficiency in classical ML algorithms and deep learning architectures. - Natural Language Processing (NLP) expertise with hands-on experience in large language models. - Proficiency in Python, relevant libraries, software development skills, and experience in MLOps principles. - Data Engineering experience with data pipelines, ETL processes, and knowledge of big data technologies. - Cloud Computing hands-on experience with platforms like AWS, Azure, or GCP, and familiarity with cloud-based ML services. This job description highlights the core responsibilities and qualifications required for the Applications Development Technology Lead Analyst role at Citi. Your contributions will not only impact the business strategy and risk management but also drive continuous improvement and innovation in the field of data analytics and machine learning. As an Applications Development Technology Lead Analyst at Citi, you will play a crucial role in establishing and implementing new or revised application systems and programs in coordination with the Technology team. Your primary responsibility will be to lead applications systems analysis and programming activities. Here is a detailed overview of what will be expected from you: Key Responsibilities: - Lead the design and execution of complex data analysis and AI/ML initiatives across large, structured, and unstructured datasets. - Develop and deploy predictive, classification, clustering, and forecasting models to support business strategy and risk management. - Partner with business stakeholders to translate requirements into analytical and machine learning solutions. - Design and implement feature engineering pipelines and model evaluation frameworks. - Collaborate with Data Engineering teams to ensure scalable data pipelines and ML-ready datasets. - Operationalize machine learning models through production deployment and monitoring (MLOps practices). - Analyze trends, anomalies, and behavioral patterns using statistical and machine learning techniques. - Ensure model governance, explainability, fairness, and compliance with regulatory requirements. - Automate analytics workflows and implement scalable AI-driven solutions. - Present analytical findings and model insights to senior leadership and cross-functional teams. - Mentor junior analysts and data scientists on advanced analytics and ML best practices. - Drive continuous improvement in analytical methodologies, model performance, and reporting standards. - Influence strategic decisions through data science and AI-powered insights. - Manage multiple priorities in a fast-paced, highly regulated environment. Qualifications Required: - 8-12 years of relevant experience in Data Analytics, Data Science, or Advanced Analytics roles. - Extensive experience in system analysis and programming of software applications. - Foundation in Machine Learning and Deep Learning, including p