Data Analytics Lead – Vice President

Citi

Data Analytics Lead overseeing data science projects and AI/ML initiatives in financial services. Integrating subject matter expertise while mentoring teams and ensuring compliance with regulatory standards.

Posted 7/16/2026full-timeIrving • Florida, Texas • 🇺🇸 United StatesSenior💰 $125,760 - $188,640 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates advanced expertise in Data Analytics and Data Science, with a strong focus on machine learning model development, deployment, and operationalization. Proven ability to communicate complex insights effectively to stakeholders while ensuring compliance and governance in analytical practices.

Highest-signal resume keywords

Data AnalyticsMachine Learning Model DevelopmentSQL ProficiencyPython ProgrammingStatistical Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data SciencePredictive ModelingFeature EngineeringModel Validation TechniquesData AnalysisAI/ML InitiativesAutomated Analytics WorkflowsData GovernanceETL ProcessesBig Data Ecosystems

Soft Skills

Analytical ThinkingProblem-SolvingStakeholder ManagementCommunication SkillsMentoring

Tools & Technologies

SQLPythonPySparkScikit-learnXGBoostTensorFlowPyTorchTableauPower BIMLOps

Industry Keywords

Financial ServicesData GovernanceModel ExplainabilityComplianceData Warehousing

Tech Stack

Tools & technologies

ETLPySparkPythonPyTorchScikit-LearnSQLTableauTensorflow

About the role

Key responsibilities & impact

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 to guide, influence and convince others
Resolves occasionally complex and highly variable issues
Produces detailed analysis of issues where the best course of action is not evident
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
Lead the design and execution of complex data analysis and AI/ML initiatives across large datasets
Develop and deploy predictive, classification, clustering, and forecasting models
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
Analyze trends, anomalies, and behavioral patterns
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

Requirements

What you’ll need

10-15 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.

Benefits

Comp & perks

medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
planned time off (vacation)
unplanned time off (sick leave)
paid holidays