Transformation Lead, AI & Automation — North America Print

HP•Houston, TX

11d•$105,050 - $161,800

About The Position

The Transformation Lead, AI & Automation converts the North America Print transformation agenda into delivered outcomes, helping the business remain competitive and adaptable. The role develops strategic recommendations by synthesizing data, conducting in-depth analysis, and testing hypotheses to support informed decisions. It improves planning and executive decision-making by removing manual, repetitive, and reconciliation-heavy work through AI, automation, and process redesign. The role leads large, cross-functional initiatives and works across businesses to align transformation efforts with organizational goals. It owns and prioritizes a diverse transformation backlog, redesigns recurring business workflows, modernizes executive reporting, and drives appropriate AI and Copilot adoption. The position establishes baselines and measures to demonstrate results, advises business executives on transformation choices and risks, and builds team capabilities so improvements can be sustained without central dependency. The role typically requires 7–10 years of work experience, preferably in data analytics, database management, statistical analysis, or a related field. A four-year or graduate degree in Mathematics, Statistics, Economics, Computer Science, or a related discipline is recommended, or commensurate work experience or demonstrated competence. The annual pay range is $105,050–$161,800 USD for U.S. candidates, with additional bonus and/or equity opportunities. HP offers a comprehensive benefits package. The position is full-time, with 25% travel; no shift premium is specified.

Requirements

Four-year or graduate degree in Mathematics, Statistics, Economics, Computer Science, or a related discipline, or commensurate work experience or demonstrated competence.
Typically 7–10 years of work experience, preferably in data analytics, database management, statistical analysis, or a related field.
Knowledge and skills in Agile Methodology, Business Intelligence, Computer Science, dashboards, data analysis, data management, data modeling, data quality, data science, data visualization, data warehousing, ETL, machine learning, Power BI, Python, R, SAS, SQL, statistics, and Tableau.
Effective communication, results orientation, learning agility, digital fluency, and customer centricity.

Nice To Haves

Programming language certification in SQL, Python, or a similar language.
Experience in data analytics, database management, statistical analysis, or a related field.

Responsibilities

Own the transformation backlog by identifying, sizing, prioritizing, and sequencing opportunities across Category, Sales, Finance, Supply Chain, Worldwide Planning, and Business Management Systems, using portfolio frameworks to evaluate and manage initiatives.
Lead Take Work Out initiatives and quantify effort removed, cycle time reduced, and error rates improved.
Redesign recurring workflows across forecast, outlook, commit, reporting, and operating-review cycles, applying the stop, simplify, standardize, automate, delegate sequence before recommending new tooling.
Modernize executive reporting and decision support, including dashboard rationalisation and standardised narrative and bridge generation.
Drive AI and Copilot adoption where it improves decision quality, speed, or consistency, and recommend against AI when the underlying process is broken or unnecessary.
Establish measurement and evidence by structuring the analytical approach, baselining the current state, defining expected benefits, and evidencing delivered results.
Lead large, cross-functional initiatives end to end by defining objectives, deliverables, guidelines, and contingency plans; manage stakeholders and communications across businesses, functions, and regions to align direction and ensure timely delivery.
Advise business executives on transformation choices, risk, and growth opportunities; follow up regularly on commitments to ensure accountability; and build wider team capability so improvements are sustained without central dependency.