The Minds Behind Bit Bros

Adam is a leader in data science, optimization, and software engineering, known for combining deep technical expertise with real-world impact. He has authored or contributed to four books with 3k+ copies sold, including "You Got The Data Job.. Now What?", "The MILP Optimization Handbook Series", and "The Decision Factory", which includes a foreword by Warren Powell and has been assigned as required reading across several major universities.

Today, Adam works at Amazon as a Senior Research Scientist in the Supply Chain Intelligence group, where he launched a new ordering model for Amazon Private Brands and applies research science to large-scale retail supply chain decisions. His work connects probabilistic forecasting, optimization, and production software to ordering, inventory, and planning decisions at Amazon scale.

At Gurobi, Adam served as a Technical Account Manager and was one of the company's first 200 employees. He helped shape the company's AI strategy, partnered with clients on top-down, executive-led decision intelligence strategies, and worked with enterprise technical teams building production decision science systems. His work included model architecture, deployment patterns, solver tuning, numerical diagnostics, and performance engineering.

At Toyota, Adam served as a Lead Decision Scientist, building decision intelligence systems for demand-supply matching, simulation, and supply chain optimization. He helped the organization navigate major supply disruption using mathematical models and supported global transformation efforts across planning, allocation, and sequential decision analytics.

Earlier in his career, Adam worked on smart mobility and autonomous vehicles at Ford, where he built custom vehicle routing problem solvers and simulation tools, co-invented a patented multimodal trip-planning application for journeys across transportation modes, and helped commercialize routing APIs for external customers including Walmart. At Infosys Consulting, he led global AI and automation initiatives for a major logistics company, helping build an Azure-scale prediction platform described internally as the second-largest prediction system on Microsoft Azure, supporting low-latency, high-throughput delivery planning and operational recommendations.

Beyond his enterprise roles, Adam has advised AI startups in the quick service restaurant industry and in governed, cross-organization agentic AI data-sharing, helping teams move from technical ideas to practical decision systems. He has also done contract work for LeetCode as a content lead, solution author, and problem author; taught AI/ML bootcamps in partnership with Caltech through Simplilearn; and consulted for DLA.