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The Data Analytics Lead Analyst is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. 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. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.
Job Responsibility:
Integrates subject matter and industry expertise within a defined area
Contributes to data analytics standards around which others will operate
Applies in-depth understanding of how data analytics collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the entire function
Employs 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
Resolves occasionally complex and highly variable issues
Produces detailed analysis of issues where the best course of action is not evident from the information available, but actions must be recommended/ taken
Responsible for volume, quality, timeliness and delivery of data science projects along with short-term planning resource planning
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:
12 - 15 years experience using codes for statistical modeling of large data sets
Strategic Data Analysis:Lead complex Bigdata analysis initiatives to identify patterns, anomalies, and opportunities for process improvement within the KYC lifecycle
Should also have strong experience on Python, Pyspark along with data governance
Insight Generation:Analyze large-scale customer and transactional datasets to generate actionable insights that enhance risk assessment models, improve operational efficiency, and strengthen compliance controls
Stakeholder Collaboration:Partner with senior stakeholders across Compliance, Technology, and Operations to understand business challenges, define analytical requirements, and present data-driven recommendations
Data-Driven Strategy:Play a key role in defining the data strategy for the KYC modernization program, including data sourcing, quality standards, and governance frameworks
Metrics & Reporting:Design, develop, and maintain advanced dashboards and reports to monitor Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs)
Provide regular updates to senior leadership on the effectiveness of KYC processes and the progress of the modernization project
Data Quality & Governance:Establish and oversee data quality frameworks to ensure the accuracy, completeness, and integrity of KYC data
Lead efforts to remediate data quality issues at their source
Advanced Analytics:Utilize statistical techniques and advanced analytical methodologies to develop predictive models for customer risk segmentation and to identify emerging financial crime typologies
Mentorship:Act as a subject matter expert and mentor for junior analysts, fostering a culture of analytical excellence and continuous learning within the team
Bachelor’s/University degree or equivalent experience, potentially Masters degree