Daniel King Email & Phone Number

Tampa, FL, US

Greater Orlando

• Engineering intelligent Cloud-based AI solutions for government and public sector clients in the Tax and Legal domain
• Served as lead data scientist for the migration of RAG components to AWS in an internal application, leveraging AWS resources to transform the application into a production-grade, enterprise-ready AI solution.

Tampa, Florida, United States

• Leveraged OpenAI to engineer a Proof-of-Concept RAG (Retrieval-Augmented Generation) system on Azure for a Fortune 500 client, combining structured SQL and unstructured data sources to deliver immediate insights during.
• Developed role-based chatbots (e.g., CEO, CFO, CTO), offering time-effective consultation options, enhancing efficiency and productivity in the workplace
• Enabled client to leverage this advanced AI solution as a sales tool, effectively demonstrating the potential for customized, production-grade applications and driving enterprise demand for LLM-driven solutions

Tampa, Florida, United States

• Collaboratively developed a propensity model in Azure ML Studio with LSTM neural networks, dissecting 5 years of sales data (85,000 instances) into seasonal sales patterns to support optimal purchasing strategies..
• Implemented and managed a mutli-stage AWS ETL pipeline using Python, S3, EC2, and Athena, handling 500-1000MB of data per day from 30+ sources, significantly enhancing data quality and availability
• Executed presentations, providing comprehensive insights on ML solutions, data analysis, and value captured, to client IT Director, Lead Analytics Engineer, SMEs, and internal stakeholders
• Conducted stakeholder interviews at client companies to understand business needs and goals, aligning data-driven solutions with strategic business objectives for optimal impact

Short Hills, New Jersey, United States

• Collaborated on a team managing Dun & Bradstreet's substantial US Business Directory, contributing to a database of hundreds of millions of records
• Enhanced data sorting algorithm, adding unique error-buckets to boost error detection and categorization accuracy
• Leveraged Python for data extraction from diverse structured/unstructured sources (CSV, TXT, Excel, JSON, XML), and utilized SQL Snowflake for data preparation, strengthening data mining abilities

Gainesville, Florida, United States

• Leveraged manual data mining techniques to identify an average of 100 potential clients per week from large-scale industry conventions in the architecture business
• Collaborated with international and domestic organizations to seek out potential clients for hired companies