Principal Data & AI Scientist | Applied AI/ML

Hybrid/Remote, Corporate Headquarters, Eden Prairie, MN | 2018 - Present

Summary

As a hybrid-role principal data scientist and full stack software engineer for the C.H. Robinson Advanced Analytics & Data Science team, I focus on rapid software prototyping, application development, integrated data systems and identifying solutions to complex problems using machine learning, AI, and automation. Heavily concentrated on data exploration and early-stage POCs, my role is to build product and applications that have a tangible impact to our bottom line. Ultimately replacing thousands of FTE hours in the process.

Project Highlights

CHRWebAgent: Agentic AI Portal Automation Read More...
Document AI: Systematic Data Extraction Tool Read More...
Generative AI for EDI Read More...
Automated ETA Scheduling & Appointment Management Read More...
TMS Machine-Driven Automated Strategic Quoting Read More...
ML System: OCR Data Extraction, Government Trucking Contracts Read More...

Press & News Coverage

At C.H. Robinson, Artificial Intelligence Has Now Performed Over 3 Million Shipping Tasks
CH Robinson expands AI use for LTL quotes, capacity acquisition
How one Minnesota Fortune 500 company is using industry-leading AI to respond faster to customers
CH Robinson gets Q1 gross profit boost from AI
C.H. Robinson leveraging AI tools to answer email requests for quotes

Strategic Impact

Proven Project Delivery & Business Impact: Consistently deliver multiple complex data science projects concurrently, resulting in significant, measurable, and positive financial outcomes for the organization.
Executive Communication & Strategic Alignment:Host weekly stand-ups with executive leadership, serving as a crucial conduit between technical engineering teams and key business units to ensure strategic alignment and effective communication of progress and insights.
AI Thought Leadership & Innovation: Recognized as a knowledge leader for my insights into the strategic adoption of AI across the enterprise, coupled with a keen ability to quickly translate innovative ideas into tangible POC/Minimum Viable Product (MVP) applications.
Platform Contribution & Enhancement: Actively contribute feature development, bug fixes, and engineering enhancements to larger organizational platforms and core repositories, fostering a collaborative development environment.
Strategic Project & KPI Leadership: Serve as an Epic Lead for data science and IT teams, overseeing key initiatives and providing comprehensive Key Performance Indicator (KPI) and metrics reporting to senior leadership.

Positions Held

Role Details

Pioneering AI Solutions: Lead early-stage software prototyping and research and development (R&D) for data-centric proof-of-concept (POC) applications, focusing on leveraging emerging AI technologies. This includes a strong emphasis on Large Language Model (LLM) and AI Engineering.
LLM and AI Engineering Specialization: Deep expertise in integrating and deploying Large Language Models (LLMs), including advanced GPT models. This involves sophisticated prompt engineering for optimal model performance, and utilizing frameworks like LangChain to build complex, context-aware AI applications. My work in AI engineering focuses on the entire lifecycle of AI systems, from research and development to deployment and maintenance, ensuring scalability, reliability, and ethical considerations.
Building High-Performing ML Teams: Successfully incubate and scale development teams of machine learning engineers, empowering them to manage, deploy, and scale critical data science applications and products that drive business value.
Cross-Functional AI Development: Collaborate with Enterprise Project Managers (EPMs), Product Managers, DevOps teams, and business stakeholders to build highly elaborate, AI-enhanced intelligent applications. These applications are designed to service and optimize operations for our global network of logistics teams.
Robust Data Pipeline Architecture: Design, automate, and maintain resilient big data pipelines and microservices, adhering strictly to Extract, Transform, Load (ETL) principles to ensure data integrity and accessibility for AI models.
Comprehensive Data Engineering: Possess deep knowledge of both relational SQL and NoSQL data engineering, with daily hands-on experience utilizing technologies such as Apache Kafka, Redis, MongoDB, PostgreSQL, MSSQL, and Snowflake.
High-Performance API Development: Develop extensive API services using modern frameworks like FastAPI, Flask, and Django, servicing both external integrations and internal teams with high-performance and scalable solutions.
Automated Deployment & CI/CD: Build and maintain robust, automated Continuous Integration/Continuous Deployment (CI/CD) pipelines for seamless deployments to Azure Kubernetes Service (AKS) and on-premise Linux virtual machines.
Python-Centric Full Stack Development: Lead Python-based full-stack software application programming, with a strong focus on leveraging open-source technologies and machine learning libraries to create innovative solutions.
Transformative Machine Learning Solutions: Develop supervised machine learning algorithms that have replaced thousands of Full-Time Equivalent (FTE) hours, significantly standardizing operations and enhancing efficiency across Robinson customers and teams.
Intelligence Automation & Data Mining: Engineer sophisticated intelligence-gathering automation tools and data mining solutions that capture, refine, and interpret critical data for competitive analysis and strategic decision-making.
Natural Language Processing (NLP) Expertise: Utilize Natural Language Processing (NLP) techniques to effectively ingest and interpret unstructured data from various sources, including document and email correspondence.