Data Analytics Lead - Vice President

Responsibilities 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 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. Core Competencies 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. #J-18808-Ljbffr Jobtailor