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Data Analytics Lead - Data Scientist - Vice President - C13

$125.76k - $188.64k

Citi

Citi seeks a VP-level data analytics leader to architect and drive advanced data analytics and AI/ML initiatives, translating business requirements into scalable solutions while upholding governance and MLOps practices. This onsite role in Tampa, FL partners with stakeholders across the organization, mentoring teams and guiding analytics strategy in a regulated financial services environment. The compensation range is USD 125,760 to 188,640 per year.

Responsibilities

  • Brings domain knowledge and industry context to defined analytics areas and directions.
  • Shapes data analytics standards that guide colleagues and teams.
  • Leverages deep understanding of how analytics fit within the sub-function and coordinates toward broader function objectives.
  • Uses advanced communication and diplomacy to influence cross-functional partners and occasional external stakeholders.
  • Addresses moderately complex, variable issues and resolves them with informed judgment.
  • Delivers in-depth analyses when the optimal path isn’t immediately evident and provides actionable recommendations.
  • Owns the delivery, quality, and timeliness of data science projects, including short-term resource planning.
  • Assesses risk in business decisions, safeguarding Citi, clients, and assets by ensuring regulatory compliance, policy adherence, ethical conduct, and transparent handling of control issues.
  • Leads the design and execution of intricate data analysis and AI/ML initiatives across structured and unstructured data.
  • Develops and deploys predictive, classification, clustering, and forecasting models to support strategy and risk management.
  • Partners with business stakeholders to convert requirements into analytical and ML solutions.
  • Designs and implements feature engineering pipelines and model evaluation frameworks.
  • Collaborates with Data Engineering to ensure scalable data pipelines and ML-ready datasets.
  • Operationalizes machine learning models through production deployment and monitoring following MLOps practices.
  • Analyzes trends, anomalies, and behavioral patterns using statistical and machine learning techniques.
  • Ensures model governance, explainability, fairness, and regulatory compliance.
  • Automates analytics workflows and scales AI-driven solutions.
  • Communicates analytical findings and model insights to senior leadership and cross-functional teams.
  • Mentors junior analysts and data scientists on advanced analytics and ML best practices.
  • Drives continuous improvement in analytical methodologies, model performance, and reporting standards.
  • Influences strategic decisions through data science and AI-driven insights.
  • Manages multiple priorities in a fast-paced, highly regulated environment.

Requirements

  • 10 to 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 experience preferred.
  • Hands-on history building and deploying machine learning models (supervised and unsupervised).
  • Experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
  • Solid 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) 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.
  • Banking or financial services experience is preferred.

Technologies

  • Python
  • PySpark
  • SQL
  • scikit-learn
  • XGBoost
  • TensorFlow
  • PyTorch
  • Tableau
  • Power BI
  • MLOps

Benefits

  • Discretionary and formulaic incentive and retention awards
  • Medical, dental & vision coverage
  • 401(k)
  • Life, accident, and disability insurance
  • Wellness programs
  • Paid time off packages (vacation, sick leave, and paid holidays)
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Vacancy posted 9 hours ago
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