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The Data Science Sr Lead Analyst is a strategic professional who closely follows latest trends in own field and adapts them for application within own job and the business. Typically a small number of people within the business that provide the same level of expertise. Excellent communication skills required in order to negotiate internally, often at a senior level. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Accountable for significant direct business results or authoritative advice regarding the operations of the business. Necessitates a degree of responsibility over technical strategy. Primarily affects a sub-function. Responsible for handling staff management issues, including resource management and allocation of work within the team/project.
Job Responsibility:
Conducts strategic data analysis, identifies insights and implications and make strategic recommendations, develops data displays that clearly communicate complex analysis
Mines and analyzes data from various banking platforms to drive optimization and improve data quality
Deliver analytics initiatives to address business problems with the ability to identify data required, assess time & effort required and establish a project plan
Consults with business clients to determine system functional specifications. Applies comprehensive understanding of how multiple areas collectively integrate to contribute towards achieving business objectives
Consults with users and clients to solve complex system issues/problems through in-depth evaluation of business processes, systems and industry standards
recommends solutions
Leads system change process from requirements through implementation
provides user and operational support of application to business users
Formulates and defines systems scope and goals for complex projects through research and fact-finding combined with an understanding of applicable business systems and industry standards
Impacts the business directly by ensuring the quality of work provided by self and others
impacts own team and closely related work teams
Considers the business implications of the application of technology to the current business environment
identifies and communicates risks and impacts
Drives communication between business leaders and IT
exhibits sound and comprehensive communication and diplomacy skills to exchange complex information
Performs other duties and functions as assigned
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
Requirements:
15+ years of relevant experience in Data Analytics, Data Science, or Advanced Analytics roles
Advanced proficiency in SQL and relational database concepts
Strong programming experience in Python (required)
PySpark 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
Bachelor’s/University degree or equivalent experience, potentially Masters degree
Master’s degree or specialization in AI/ML/Data Science preferred
Nice to have:
PySpark
Familiarity with MLOps practices (model deployment, monitoring, versioning)
Experience in banking or financial services
Master’s degree or specialization in AI/ML/Data Science