AI Driven Automation & Cognitive Solutions [Health Services]- Manager

PricewaterhouseCoopers•Chicago, IL

2d•Remote

About The Position

As an AI Driven Automation & Cognitive Solutions Manager, you will lead client-facing work in artificial intelligence engineering, helping design and deliver automation and cognitive solutions within our Data and Analytics Engineering practice. As a Manager, you will motivate and develop teams, guide workstreams, and bring business insight to complex delivery challenges while applying technology and innovation to support client needs. In this role at PwC, you will work across AI and machine learning efforts focused on algorithm design, model development, and intelligent process automation for the health services sector, while coaching team members, reviewing deliverables, and supporting steady progress on client engagements.

Requirements

At least a Bachelor's degree
At least 5 years of experience

Nice To Haves

Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
Leading AI automation initiatives across client service engagements
Managing project plans, budgets, timelines, and deliverables
Mentoring teams in data and AI delivery methods
Applying Python, data analysis, and machine learning skills
Navigating health services transformation and cross-functional stakeholder needs

Responsibilities

Leading AI-driven automation and cognitive solution workstreams for health services clients
Managing project planning, budgeting, execution, and delivery timelines across assigned engagements
Guiding teams in designing and developing AI and machine learning models, algorithms, and intelligent automation solutions
Reviewing complex data analysis and Python-based code to validate model performance, data integrity, and implementation readiness
Coaching team members in technical problem solving, programming approaches, and applied AI implementation methods
Collaborating with client stakeholders to identify automation opportunities and translate business needs into technical solutions
Monitoring deliverables across multiple workstreams, resolving issues, and escalating risks when needed
Reinforcing professional and technical standards while promoting responsible use of AI and data solutions