AI & Analytics Project Manager

EXL

About The Position

Responsibilities split by time: 50% Stakeholder Workshop Facilitation: Proven experience designing and running stakeholder workshops for analytics requirements gathering, with the ability to engage senior leaders (VPs, Directors, Senior Directors). Also responsible for documenting session outputs and producing executive-level slides for leadership summaries. Conflict Management & Consensus Building: Demonstrated ability to manage conflicting viewpoints among senior stakeholders and drive discussions toward a productive consensus, keeping the group aligned on shared goals. KPI Definition & Prioritization: Experience helping stakeholders define, refine, and prioritize KPIs and requirements so that value can be delivered incrementally while maintaining a clear and visible roadmap. Executive Communication & Storytelling: Ability to present KPI roadmaps, progress updates, and readouts to senior leadership, distilling complex technical challenges into clear, simple language and proposing actionable solutions. Stakeholder Management & Pushback: Confidence and credibility to challenge senior leaders when requirements are unrealistic, overly ambitious, or technically unfeasible, ensuring alignment between business expectations and delivery capacity. 50% AI and BI Program Expertise: Solid understanding of how to drive AI (RAG) Programs/Products and Business Intelligence Program/Products from both a strategic and operational standpoint. Data Source Identification: Ability to work with client data leaders to identify the data sources required to create the defined KPIs. Data Storytelling & Architecture: Ability to think through how datasets should be stitched together to tell a coherent story that helps senior leaders understand the current state of their programs, surface key challenges, and enable course correction. Technical Translation & Documentation: Ability to translate business and analytics requirements into clear specifications for the data engineering and BI teams, including explaining what the final data outputs should look like, how dashboards should be structured, and how navigation should flow from landing pages to detailed views. Technical Literacy: Working knowledge of key concepts across data engineering, data pipelines, business intelligence, and AI/RAG solutions, enabling effective collaboration with technical teams across all workstreams. Quality Evaluation & Validation: Ability to validate datasets and dashboards against defined requirements, clearly communicate gaps to the technical team, and collaborate with AI developers to improve output quality by suggesting appropriate guardrails and corrective measures.

Requirements

8+ years of experience in analytics strategy, data strategy, AI/ML strategy, or digital transformation advisory.
Significant client-facing experience, including presenting to senior executives and influencing strategic decisions.
Strong understanding of modern data platforms, analytics tools, governance, and AI/ML capabilities—with the ability to discuss at a strategic level.
Outstanding communication, executive storytelling, and facilitation skills.
Proven ability to structure ambiguity, lead enterprise assessments, and develop clear, actionable strategies.
Experience leading multi-disciplinary teams and managing complex stakeholder groups.