Victor Foster

AI/ML Solutions Engineer

Bridging technical AI/ML capabilities with real-world business results. 20+ years across logistics, B2B technical sales, and entrepreneurial consulting—now applying AI to solve complex problems across diverse domains.

Victor Foster

About Me

I bridge technical AI/ML capabilities with real-world business applications.

With over 20 years of experience across logistics operations, B2B technical sales, entrepreneurial consulting, and security systems, I bring a unique perspective to AI/ML solutions engineering. My diverse background has developed essential skills: translating technical features into business value, managing client relationships, coordinating cross-functional teams, and rapidly learning new domains.

Currently completing TripleTen's AI/ML Engineering bootcamp, I specialize in understanding client business problems, designing AI/ML solutions that address real-world constraints, and managing implementation projects from discovery to deployment.

My unique combination allows me to speak both technical and business languages fluently—ensuring AI/ML implementations that drive adoption, demonstrate value, and deliver measurable results. View my full resume →

20+

Years of Professional Experience

AI/ML

Solutions Engineer

Multi-Industry

Problem Solver

Featured Projects

AI/ML and data science projects demonstrating technical problem-solving and business value delivery

Video Game Sales Forecasting

Forecasting

Analyzed 35+ years of gaming industry sales data to forecast 2017 product success across platforms, regions, and genres. Built statistical models to identify success patterns, then translated complex findings into clear marketing recommendations that non-technical teams can act on immediately.

Python Pandas Matplotlib SciPy

Megaline Statistical Analysis

Statistics

Applied statistical hypothesis testing to analyze telecom customer behavior across 5 datasets. Converted technical statistical outputs (p-values, confidence intervals) into a clear executive recommendation on which calling plan to prioritize—bridging technical analysis and business decision-making.

Python NumPy SciPy Statistics

Instacart Market Basket Analysis

EDA

Analyzed 30 million grocery transactions by systematically connecting 5 datasets to uncover customer shopping patterns—purchase timing, product pairings, and reorder behavior. Delivered insights in a Jupyter notebook designed for product managers to understand and act on immediately.

Python Pandas Matplotlib
View All Projects

Technical Skills

Languages & Core

Python SQL Bash

Data Analysis

Pandas NumPy Matplotlib Jupyter

Machine Learning

Scikit-learn TensorFlow PyTorch Keras LightGBM

NLP & AI

NLTK HuggingFace LLMs

Big Data & Cloud

PySpark AWS

DevOps & APIs

Docker Kubernetes Flask FastAPI

Get In Touch

Interested in working together? Let's connect.