About OptiML AI
Expertise at the intersection of optimization, machine learning, and artificial intelligence
Warren Hearnes, PhD
Founder & CEO
Warren is an AI/ML Executive with extensive experience leading data science teams and implementing AI solutions across multiple industries. Prior to founding OptiML AI, he served as Chief Data Scientist at Best Buy and SVP of Analytics & Data Science at Cardlytics.
With a PhD in Industrial Engineering and MS in Operations Research from Georgia Tech, Warren has been at the forefront of machine learning since its early stages in the 1990s. His expertise spans the use of optimization to make better decisions and artificial intelligence/machine learning to derive value from business data.
Warren is a published author, invited speaker, and has been recognized with awards for outstanding academic research, industry innovation, volunteer service, and military excellence.
Professional Background
Vice President, Head of Data Science | Chief Data Scientist
Best Buy
2022 - 2024
- Led a team of 45+ data scientists that elevated the use of data science across the enterprise.
- Created the company's AI Strategy, setting guiding principles and high-level roadmap for implementing all types of AI, ML, and optimization to solve business problems.
- Implemented an Analytics Product Lifecycle Framework for creating scalable and repeatable analytics solutions. This initiative has clarified roles, improved project focus, and facilitated the deployment of analytics solutions.
Senior Vice President, Analytics & Data Science | Chief Analytics Officer
Cardlytics
2011 - 2021
- Led a team of 75+ analysts & data scientists responsible for answering analytical questions, cleaning/QA of internal data, BI, & data science for core products.
- Set and executed analytics/data science strategy that helped propel CDLX from start-up to multi-billion dollar public company.
- Developed state-of-the-art AI/ML approaches that served as the foundation for targeted marketing platform.
- Responsible for the analytics consulting and deliverables for the advertising clients that used the CDLX platform.
- Responsible for all revenue-generating algorithmic development, measurement, and scalable solutions.
Manager, Marketing Sciences
The Home Depot
2011 - 2011
- Recruited to build and lead the in-house CRM analytics team for direct mail and email marketing for The Home Depot.
- Led the development of advanced analytical models for customer response and uplift after receiving direct mail/email communications, as well as “next recommended product” engines for 1-to-1 communications.
- Led the analytics effort to incorporate primary research for the Pro segment into a model enhancement for more precise Pro vs. Consumer segmentation.
- Led an analytics effort to build a CLV model based on statistical methods that estimate the purchase frequency and transaction value for every customer, helping target the most valuable customers and tailor communications to correct segments.
Manager, Marketing Sciences
UPS
2003 - 2011
- Led the development of patented pricing algorithms managing over $10B in revenue
- Worked with corporate Transportation Finance to develop spreadsheet-based tools that minimized costs, conducted “what if?” scenarios, and determined price points of various movement alternatives.
- Worked with UPS Healthcare Logistics to develop a patented approach for identifying orders of controlled substances that are “unusually large or frequent”, as required by federal regulations.
- Worked with Corporate Credit to identify risky new accounts opened through UPS.com. Prioritized investigative efforts by impact on revenue.
- Generated "target lists" through standard commercial packages or customized internal algorithms for various groups within the corporate HQ to discern which subset of the potential customers are more likely to react positively to a campaign or product.
Member of Technical Staff
Lucent Technologies/OFS
1998 - 2003
- Managed the company’s main resource -- fiber inventory.
- Led the operation and improvement of an optimization model that allocated inventory to orders in the most profitable manner.
- Established parameters for “useable” inventory and developed web-based tools for identifying and fixing problems.
Education
PhD
Industrial Engineering
Georgia Institute of Technology
Research focus on machine learning, reinforcement learning, and optimization for complex systems.
MS
Operations Research
Georgia Institute of Technology
Specialized in mathematical optimization, stochastic processes, and decision analysis.
BS
Mathematics - Operations Research
United States Military Academy at West Point
Graduated in the top 5% of class.
Technical Expertise
Integer Programming
Integer Programming (IP) is a powerful mathematical optimization technique that Warren has applied extensively throughout his career to solve complex business problems. Unlike continuous optimization, integer programming deals with decision variables that must take integer values, making it ideal for many real-world scenarios.
Applications
- Production planning and scheduling
- Resource allocation and workforce planning
- Re-balancing assets
- Vehicle routing and logistics optimization
Modeling
- Open-source and commercial solvers
- Open-source and commercial modeling languages
- Parameter tuning
- Python-based modeling
Warren has implemented integer programming solutions that have generated millions in cost savings and revenue optimization for Fortune 500 companies. His approach combines theoretical rigor with practical implementation, ensuring solutions that are both mathematically sound and business-relevant.
Large Language Models (LLMs)
Large Language Models (LLMs) represent the cutting edge of artificial intelligence, and Warren has been at the forefront of their application in business contexts. These powerful models have transformed how businesses interact with data, customers, and information systems.
Business Applications
- Intelligent customer service automation
- Content generation and summarization
- Knowledge management and information retrieval
- Data analysis and insight generation
- Process automation and workflow enhancement
Implementation Expertise
- Application for specific business domains
- Prompt engineering and optimization
- Retrieval-augmented generation (RAG) systems
- Responsible AI implementation and governance
- Integration with existing business systems
Warren's approach to LLMs goes beyond the hype, focusing on practical, value-driven implementations that deliver measurable business results. He has helped organizations navigate the complexities of LLM deployment, from model selection and fine-tuning to integration and governance, ensuring solutions that are both powerful and responsible.
Machine Learning
With over two decades of experience in machine learning, Warren brings a depth of expertise that spans the evolution of the field from its early applications to today's advanced techniques. His work has consistently focused on translating complex algorithms into practical business solutions.
Predictive Analytics
- Time series forecasting
- Customer behavior prediction
- Demand planning
- Risk assessment models
- Anomaly detection systems
Machine Learning
- Neural network architecture design
- Computer vision applications
- Natural language processing
- Reinforcement learning systems
ML Operations
- Model deployment pipelines
- Performance monitoring
- Model governance
- Scalable ML infrastructure
- Continuous training workflows
Warren's machine learning expertise is distinguished by his ability to bridge the gap between theoretical understanding and practical implementation. He has successfully led teams in developing and deploying machine learning solutions across diverse industries, consistently delivering measurable business impact.
His approach emphasizes not just the technical aspects of machine learning, but also the organizational and cultural changes needed to successfully integrate AI into business operations. This holistic perspective ensures that machine learning initiatives deliver sustainable value and drive meaningful transformation.
Ready to Transform Your Business with AI?
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