Bio
Mr. Conner Schultz is an environmental consultant with experience in data collection, analysis, and management and in GIS. He extends his use of applications, such as ArcGIS and QGIS, with additional programming languages that include SQL and MATLAB®, to perform quantitative analyses and to develop supporting data visualizations. Mr. Schultz assists in analyzing both spatial and non-spatial data for a variety of projects, including environmental risk assessments, natural resource damage assessments, and RI/FSs. Since joining Integral in early 2019, he has been a contributing member to Integral’s sediment profile and plan view imaging (SPI–PV) data processing team. He supports the planning and design of SPI–PV field surveys, conducts image analysis, manages SPI–PV data post-processing and leads the GIS support. He also manages the development team responsible for analysis and visualization tools and has performed analyses to support the development of custom image processing algorithms using deep learning and machine learning methodologies. In addition, Mr. Schultz has served as a project manager for seven projects with responsibilities that include management of the technical team, cost management, resource allocation, and successful deliverable tracking and client communication.
Relevant Experience
Environmental Impact Assessment
Offshore Wind
Data Analysis
Sampling
Site Assessment
Modeling
GIS Design
Ecological Modeling
Project Management
Groundwater Sampling
Site Investigation
Natural Resource Damage Assessment
Environment, Social and Governance
Education & Credentials
B.A., Environmental Business, University of Redlands, Redlands, California, 2016
Continuing Education
Coursera AI for Everyone (2018)
MATLAB Deep Learning Onramp (2018)
Hazardous Waste Operations and Emergency Response 40-Hour Certification (2019; refreshers 2020 to present)
Basic Offshore Safety Induction and Emergency Training (including Helicopter Underwater Escape Training and Emergency Breathing System) (2020)
First Aid and CPR certified (current)
Transportation Worker Identification Credential (current)
Professional Affiliations
Member of Young Environmental Professionals
Insights & News
Using Machine Learning to Efficiently Deliver CMECS Compliant Benthic Habitat Maps
Using Ecological Risk Assessment to Assess EMF Impacts to Marine Life From Offshore Wind Infrastructure