Daniel Gremmell
Chief Data Officer at Zinnia and Policygenius Inc
- Role
- Chief Data Officer at Zinnia
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Daniel Gremmell
Data driven executive whose focus is on expanding data science throughout an organization. Deep experience in implementing data science in marketing, operations and supply chain and content driven areas of a business such as editorial and culinary. Business Science Solutions is a transformation company whose focus is to revolutionize our client’s businesses through solving problems with data science. Business Science Solutions offers its customers expertise to transform a company by eliminating inefficient processes, optimizing existing ones and connecting the method to the data. We perform project by project work, training and workshops or reshape the organization to drive a complete business transformation. Our techniques include elements of data science, statistical principles, industrial engineering, business process engineering, operations research and mathematics. We want to help you optimize your business today.
Experience
Chief Data Officer
Aug 2023 — Present · New York, NY, US
Education
Kettering University
MS Manufacturing Engineering
Thomas Edison State University
Bachelors, Business Management
Rochester Institute of Technology
MS Statistics, Machine Learning
Skills
- Sales Operations
- Customer Service
- Logistics
- New Business Development
- Account Management
- Merchandising
- Linear Regression
- Manufacturing
- Product Development
- Data Science
- Supply Chain Management
- Statistical Data Analysis
- Regression Analysis
- Purchasing
- Process Improvement
- Data Mining
- Team Building
- Management
- Logistic Regression
- Retail
- Lean Manufacturing
- Deep Learning
- Python
- Forecasting
- Key Account Development
- Cross-Functional Team Leadership
- Computer Vision
- R
- Artificial Intelligence
- Sales
- Strategic Planning
- Consumer Products
- Machine Learning
- Sales Management
- Statistics
- Artificial Neural Networks
- Inventory Management
- Data Analysis
- Six Sigma
- Industrial Engineering
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