Senior AI, Data & Engineering Executive

Builds and transforms AI, data, analytics, and engineering organizations into durable business capability.

Ed Wiley is a Stanford-trained quantitative leader and McKinsey-honed strategist with a record spanning Fortune 50, large private enterprise, public-sector innovation, and venture-backed startups. He is most often brought in when organizations have invested materially in AI or data but need sharper operating models, stronger leadership, and measurable commercial outcomes.

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$150M+projected margin opportunity at Sears/Kmart

$7M+annual cost takeout at Delaware North

35%budget reduction in enterprise data and analytics

5x fasterprocessing at 85% lower compute cost

>96%faster DEA lead identification

Senior operator for moments that require more than technical fluency: building teams, resetting underperforming functions, gaining executive alignment, and turning AI ambition into execution.

Selected Impact

Repeated delivery across enterprise transformation, startup execution, and AI operating-model design.

Across sectors and company stages, Ed’s work follows a familiar pattern: clarify where value will come from, reshape the organization around that reality, and then drive the technical and operational changes required to capture it.

Enterprise transformation

Delaware North — enterprise data and analytics reset for a $4.5B hospitality company

Took over a 75-person function after six years and more than $50M of prior investment had not produced sufficient business value. Re-architected the operating model, flattened management, rebuilt the platform, and reoriented the function toward delivery and adoption.

Executed more than $7M in annual cost takeout and reduced budget by 35%.
Enabled a platform rebuild that increased processing speed 5x at 85% lower compute cost.
Cut roughly $4M in labor spend in a major business unit and launched AI acceleration with 20 business leaders.

Commercial AI at scale

Sears Holdings — machine learning-based pricing and promotions at Fortune 50 scale

Built the company’s first centralized data science organization and partnered directly with the CEO and business leaders to establish a new price-optimization capability across product lines.

Scaled the team from one analyst to 41 data scientists and ML engineers.
Pilot categories delivered margin gains of 2.54%, 2.23%, and 6.48%.
Full deployment was projected to drive more than $150M in incremental margin.

Startup CTO execution

Opsis Health — rebuilt product, engineering, and ML after a failed two-year build

Stepped in after multiple contractors had consumed significant time and capital with little progress. Rebuilt the team, architecture, and delivery motion to put the business on a credible operating footing.

Cut more than $8M in annual contractor spend.
Re-architected the product from a monolith to cloud-native microservices.
Delivered the first product to market in less than four months.

Operational ML in healthcare

Nurx — first production ML capability for a high-growth digital health company

Built the company’s ML function and delivered NLP-based routing and prioritization models that improved clinical operations while preserving care quality during rapid growth.

Created ML infrastructure for production use cases including routing and prescription optimization.
Reduced provider response times by an average of 60%.
Established the cloud architecture that later hosted subsequent ML models.

Public-sector mission impact

PenLink / DEA — analytics platform that dramatically accelerated investigative lead generation

Led innovation and analytics efforts for law-enforcement software supporting agencies including DEA, FBI, US Secret Service, and US Marshals.

Built a cloud-based analytics solution that reduced DEA lead identification time from days to minutes.
Brought PenLink’s first SaaS product to market in under six months.
Acquired more than 200 federal, state, and local agency users in the first year.

GenAI value capture

Enterprise advisory work — GenAI productivity, org design, and operating-model decisions

Advises CFOs, CTOs, CHROs, and presidents on where GenAI can create value, how to organize for delivery, and how to avoid implementation paths that consume budget without creating durable capability.

Identified approximately $50M annualized hard-cost opportunity for a large financial services organization.
Helped leaders prioritize use cases, architecture choices, and phased implementation paths.
Supported AI and data transformations that contributed to DTC e-commerce growth of more than 100% and domestic retail growth above 20%.

Executive Bio

A leadership profile built at the intersection of technical depth, operating responsibility, and commercial judgment.

Ed brings together Stanford PhD-level quantitative rigor, McKinsey strategy formation, and repeated operating experience inside organizations that needed AI, data, and engineering to become real business functions rather than isolated technical efforts.

Senior Vice President, Data & Analytics — Delaware North

2024–2025

Led a 75-person data, analytics, and labor-management organization for a $4.5B hospitality company; drove cost takeout, platform modernization, AI acceleration, and operating-model redesign.

Founder / Principal — Ed Wiley Ventures

2008–Present

Advises C-suite leaders across multibillion-dollar enterprises on AI, analytics, data strategy, operating model, organizational design, GenAI value capture, and implementation sequencing.

Chief Technology Officer — Opsis Health; Enveda Biosciences

2020–2023

Led engineering, machine learning, and product rebuilds in venture-backed health and biotech settings, including architecture redesign, team assembly, operating cadence, and fundraising support.

Vice President, Data & Machine Learning — Nurx

2019–2020

Built and led the company’s machine learning function to improve operational throughput and patient response times while scaling care delivery for a fast-growing digital health business.

Chief Innovation Officer / Chief Data Scientist — PenLink

2016–2019

Led innovation, data science, and cloud transformation for software serving leading federal, state, and local law-enforcement agencies.

Chief Data Scientist, Pricing & Promotions — Sears Holdings

2015–2016

Built a 41-person data science organization and launched machine learning-based price and promotion optimization in direct partnership with enterprise leadership.

Head of Big Data Analytics — Seagate Technology

2013–2015

Built Seagate’s first Big Data Analytics team and helped position next-generation cloud and analytics capabilities as strategic enterprise assets.

Chair & Assistant Professor — University of Colorado Boulder

2004–2011

Chaired a doctoral program, led faculty and students, taught advanced quantitative methods, and built a substantial body of research, publication, and advisory work.

Senior Strategy Associate — McKinsey & Company

2001–2004

Advised clients on strategy, innovation, pricing, organization, and investment questions—forming the commercial and strategic instincts that continue to shape executive leadership style.

Leadership

Ed is the kind of executive who can enter a complex situation, earn trust quickly, and move an organization from AI ambition to operating reality.

He has done that with CEOs, CFOs, BU presidents, startup founders, long-tenured pricing leaders, engineering organizations, and public-sector stakeholders. The pattern is consistent: build the right team, simplify the decision path, make the architecture choices that fit the business, and create a model that can scale.

Range

Comfortable across Fortune 50, large private enterprise, public sector, and startup environments

That breadth matters because it signals judgment that transfers across industry, scale, and organizational maturity rather than succeeding in only one context.

Team building

Repeatedly recruits and organizes high-caliber technical teams

From Sears to Seagate to venture-backed startups, he has repeatedly built teams capable of delivering when the company needs both execution speed and stronger technical standards.

Stakeholder leadership

Earns alignment from executives and skeptics alike

His work often requires influencing leaders who are accountable for outcomes but cautious about change, then helping them commit to a practical path forward.

Commercial focus

Frames AI decisions through economics, not theater

Cost takeout, margin expansion, throughput, labor efficiency, and organizational readiness are recurring themes across both operator and advisory work.

Architecture and delivery

Connects technical choices to execution reality

Comfortable operating from LLM strategy and vendor selection down to cloud architecture, microservices decisions, and production machine-learning infrastructure.

Executive presence

Combines Stanford PhD-level rigor with McKinsey strategy fluency

The result is a leader who can engage at board, C-suite, and technical levels without sacrificing either substance or commercial clarity.

Thought Leadership

His public voice reinforces what his operating record already shows: depth, range, and the ability to translate complexity into action.

Executive education, speaking, academic leadership, and publication history matter here because they demonstrate not just expertise, but the ability to help other leaders understand what must change for AI to succeed inside the enterprise.

Executive education

Creator of Udacity executive programs on data science and generative AI

Developed and taught “Data Science for Business Leaders” and “Generative AI for Business Leaders,” translating complex technical concepts into implementation-oriented guidance for senior business audiences.

Academic depth

Stanford PhD/MS and former doctoral-program chair

Brings unusual quantitative depth, teaching experience, and publication history, including leadership of a doctoral program and extensive research and advisory work.

Field perspective

Long view on both traditional AI and generative AI

He has worked with AI as researcher, consultant, executive, professor, advisor, and founder—creating a perspective that is both historically informed and sharply practical.

Contact

For executive searches, transformation mandates, board conversations, and high-stakes AI leadership roles.

Ed is best suited to organizations that need more than a technical specialist: a senior leader who can align executives, build or reset capability, and create measurable business value from AI, data, analytics, and engineering.

Email Ed LinkedIn Download Resume

Emailed@edwiley.ai
LocationBoulder, Colorado
LinkedIn/in/EdWileyPhD
Best fitCxO / SVP searches, operating advisory, AI transformation, board and investor conversations