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The Applications Development Technology Lead Analyst is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.
Job Responsibility:
Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements
Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards
Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint
Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation
Develop comprehensive knowledge of how areas of business, such as architecture and infrastructure, integrate to accomplish business goals
Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions
Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency
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
Build and maintain advanced dashboards, KPIs, and automated reporting frameworks to monitor business performance
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
Requirements:
At least 6+ years of relevant experience in Data Analytics, Data Science, or Advanced Analytics roles
Extensive experience in system analysis and in programming of software applications
Experience in managing and implementing successful projects
Subject Matter Expert (SME) in at least one area of Applications Development
Ability to adjust priorities quickly as circumstances dictate
Demonstrated leadership and project management skills
Consistently demonstrates clear and concise written and verbal communication
Advanced proficiency in SQL and relational database concepts
Strong programming experience in Python (required)
PySpark or R preferred
Hands-on experience building and deploying machine learning models (supervised and unsupervised)
Experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch
Strong knowledge of statistical modeling, feature engineering, and model validation techniques
Experience with BI tools such as Tableau or Power BI
Familiarity with MLOps practices (model deployment, monitoring, versioning) is strongly preferred
Experience working with large-scale enterprise or financial datasets
Understanding of data warehousing, ETL, and big data ecosystems
Strong problem-solving, analytical thinking, and stakeholder management skills
Proven ability to communicate complex AI/ML insights to non-technical audiences
Experience in banking or financial services preferred
Knowledge of model risk management or regulatory analytics is a plus
Bachelor’s degree/University degree or equivalent experience, specialization in AI/ML/Data Science preferred
Nice to have:
Experience in banking or financial services preferred
Knowledge of model risk management or regulatory analytics is a plus
PySpark or R preferred
What we offer:
medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
discretionary and formulaic incentive and retention awards