Lead Specialist, Data & Artificial Intelligence Delivery Management

Role Overview

Key Responsibilities

• Lead the end-to-end development of machine learning, AI, and advanced analytics solutions that address high-value business challenges.
• Deliver scalable, production-ready models that improve operational efficiency, reliability, productivity, and decision-making.
• Translate business priorities into actionable analytics opportunities, value hypotheses, and implementation roadmaps.
• Identify, prioritize, and develop AI and analytics use cases that deliver measurable operational and financial outcomes.
• Establish clear success measures, KPIs, and value realization frameworks for analytical initiatives.
• Enable seamless deployment of analytical models into enterprise systems, operational platforms, and digital environments.
• Strengthen model reliability and scalability through effective MLOps practices, lifecycle management, and monitoring standards.
• Partner with Data Engineering teams to improve analytical environments, data pipelines, and model readiness.
• Ensure data assets meet enterprise requirements for accuracy, integrity, security, and compliance.
• Embed responsible AI principles, governance controls, and quality standards across analytical solutions.
• Build strong partnerships with business, technology, and Data & AI stakeholders to accelerate solution adoption.
• Communicate analytical insights, risks, recommendations, and outcomes through compelling narratives and visualizations.

Minimum Qualifications

• Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Artificial Intelligence, or a related quantitative discipline.
• 6-8 years of experience in data science, machine learning, advanced analytics, or AI-related roles.
• Experience developing and deploying production-grade analytical and machine learning solutions.
• Experience translating business problems into analytical frameworks, predictive models, and actionable recommendations.
• Experience working with cross-functional business, technology, and data teams in complex organizational environments.

Skills That Matter

• Machine Learning & Artificial Intelligence
• Predictive Analytics & Statistical Modeling
• Data Mining & Pattern Discovery
• Feature Engineering & Model Optimization
• Data Visualization & Analytical Storytelling
• AI Solution Design & Industrialization
• Python, SQL & Advanced Analytics Tools
• MLOps & Model Lifecycle Management
• Data Pipeline & Analytical Environment Design
• AI Product Delivery & Value Realization
• Data Governance & Compliance
• Performance Measurement & KPI Development

Success Measures