Database Technologies (DBT) was founded based on Mark’s strong belief in clean database architecture and innovative, needs-based product development. His impressive career grew from a well-rounded skill set of database architecture, mathematical modeling and strategic marketing.



Mark holds a Master of Philosophy degree, plus a Master of Science degree and Bachelor of Science in Industrial Engineering and Operations Research from Columbia University as well as a Bachelor of Arts degree in mathematics from Grinnell College.

  • Database Architecture 99%
  • Mathematical Modeling 95%
  • Strategic Marketing 90%



New Product Development and Consulting Services Manager

  • Marketing position with the task of leading the company to a consensus on a strategic new product and working with partners to fund the development and marketing of the product.
  • Managed marketing strategies projects including: Market share, revenue per segment, and alternate distribution channel analysis and new proud t demand forecasting and consumption modeling.

Director Database Development 

  • Responsible for two departments, a 12-person staff, a $100M+ budget and the product design and development of the company’s primary asset, the Trinet National File.
  • Authored Database Development Plan – led an inter-departmental task force to determine the most pressing needs and formulated over a dozen projects, down to the task level, to provide a major quality upgrade to the core product of the company
  • Directed a two-year software effort to automate the update process resulting in high quality, fool-proof, system updates and reduced elapsed time for updates from 12 weeks to three with no increase in production costs.


Staff Manager-Market Research and Forecasting

  • Managed a group responsible for business planning, corporate facilities forecasting and regulatory support for terrestrial and satellite T1 products
  • Designed and built an automated forecasting system that was unusually accurate out to at least five years
  • LP based buying algorithm using conjoint analysis of the market research data
  • Simulation based forecasting to allow economic growth, price and buying behavior analysis