Associate Director, AI & Automation Strategy

Purpose
We are seeking an Associate Director of AI & Automation Strategy to join the Finance Transformation team. The Associate Director will be responsible for supporting AI & Automation programs across the Finance organization with a specific focus on leading adoption and enablement efforts. You will lead the development of Proofs of Concept (“POCs”), including machine learning and forecasting solutions, and the scaling of initiatives across the organization. This role will also be responsible for supporting Finance strategy in alignment with AbbVie’s Enterprise vision.
This role will team and collaborate with the wider Finance Transformation and AbbVie Business Technology Systems (“BTS”) organization to develop a comprehensive training and communications program to promote data democratization and build Machine Learning (“ML”) and Agentic AI (“GenAI”) skills across the Finance organization.
Responsibilities
Support the execution of the AI strategy in the Finance function.
Lead adoption efforts for Finance AI & Automation initiatives, including piloting solutions, collecting feedback, and ensuring successful rollout to end-users.
Lead and mentor a team of data scientists, providing technical guidance, setting priorities, and fostering best practices in model development.
Review machine learning models for quality, rigor, and business relevance before they move to production.
Partner with BTS and Machine Learning Operations (MLOps) teams to deploy, monitor, and maintain ML models in production environments.
Design and deliver ML training to build AI literacy and skills across Finance.
Help coordinate and drive communications and training to support data democratization and GenAI skill building within the Finance organization.
Assist with the creation and maintenance of a multi-year roadmap for Finance data and AI capabilities.
Collaborate closely with the Finance Transformation Data Strategy team and other business partners to rationalize data and support a central data architecture.
Support development, documentation, and adherence to governance frameworks as established by leadership.
Work with leaders and key stakeholders across Finance to identify, prioritize, and support delivery of data and AI-driven opportunities, managing expectations and communicating progress and impact.
Facilitate a culture of innovation, delivery, and measurable business impact through mentorship and promotion of best practices.
Build strong relationships across Finance, Business Technology Systems (BTS), and business unit teams to support coordination and adoption.
Ensure data is managed in compliance with regulations and company standards.
The ideal candidate will:
Execute the Finance Automation & AI strategy and influence decision-makers while leading data change management efforts across the Finance organization.
Bring hands-on ML and MLOps expertise to lead data science teams and turn models into adopted, scaled solutions.
Drive an effective data-driven culture that scales to meet the needs of all Finance functions across AbbVie.
Bachelor’s degree in Mathematics, Statistics, Data Science, Information Technology, or a related field.
Minimum 8+ years of progressive experience with exposure to data, AI, or automation programs; experience supporting or enabling data and AI initiatives preferred.
Experience building machine learning models and deploying them into production environments.
Hands-on experience with MLOps practices, including model deployment, monitoring, versioning, and lifecycle management.
Proven experience driving AI adoption, including piloting solutions, change management, user training, and scaling tools across an organization.
Familiarity with data strategy, architecture, and operations; proven success driving or supporting enterprise data initiatives as part of a larger program team.
Strong financial acumen and understanding of financial systems and processes.
Excellent collaboration, communication, and stakeholder management skills.
Ability to explain technical concepts to non-technical stakeholders and drive adoption through training and enablement.
Experience supporting multiple concurrent projects in fast-paced, changing environments.
Demonstrated ability to work independently and as part of a cross-functional team.
Strong analytical and problem-solving skills, with attention to detail and a focus on execution.

Skills
Machine Learning, Documentation

Employment type
Full-time

Work arrangement
Hybrid