Peter Jaumann

About Peter Jaumann

Visionary, leading and enthusiastic \'ground breaker\' executive; very focused and results-driven team management and strong biculturally-rooted leadership with an eye for the overall, big picture yet impeccable proclivity for the technical details and technical excellence; always on the innovative and creative edge; first-order business and technical problem solver; no nonsense approach EXPERTISE: Analytical thought leadership; data science/ML/AI strategy journey; org structuring for DS around people, process, technology, data and culture. Big data; customer-centric advanced/predictive analytics; machine learning algorithms, deep learning and AI; retail analytics; data management; strong hi-tech B2B and B2C knowledge NEW ANALYTIC PRODUCT DEVELOPMENT: 4 Pending patents with the US-PTO \'KaufPac\' and Intelligent Cube (IC): A next-generation, innovative customer analytics package comprising a. time-purchasing vector analyses, b. purchase pattern associations (static and sequential), c. next-logical purchase predictions, d. customer analogues / similarities, and e. data insight modules. Results indicate high prediction fidelity \"StreakPac\": A derivative of \'KaufPac\' adapted to the sports world. Makes use of winning/loosing streaks over time.\'FuzzyMatch\': An iterative fuzzy-logic algorithm aimed at matching customer as well as product names, de-duping, ad-hoc cleaning and attribution tasks. Makes extensive use of similarity/distance metrics, shortest common strings (via a binary search method), accurracy/confidence metric calculations as well as a variety of other adaptations such as extensive cleaning/parsing and working on different customer hierarchy levels.

Experience

1. Sr Manager Ai Captain

   Capgemini

   Sep 2017 — Present · Denver, CO, US

   Peter belongs to Capgemini\'s Data Science & Artificial Intelligence North America practice. He enjoys and excels in his 25-yr deep academic and professional career in advanced analytics, ML/AI, deep learning, data science strategy, data monetization and numerous advisory roles. Creative solutions in manufacturing, natural resources, services and telecom are his signature skills delivering novel insights, actionable recommendations and realistic strategies in the areas of supply chain integration, intelligent industries (IoT), strategic data science, MLOps/AIOps, intelligent operations and business transformation journeys. Specific focal areas revolve around stochastic simulations, network optimization, new analytic approaches and solutions as well as optimal ways to execute data science with AutoML

Education

• Brown University

  M.Sc.

  1989 — 1991

• National Center for Atmospheric Research (NCAR)

  Postdoctoral Fellow

  1995 — 1997

• University of Iowa

  Ph.D.

  1991 — 1995