AI and workflow transformation
Evaluating LLM capabilities, creating adoption roadmaps, and operationalizing AI-assisted development with guardrails, validation, and measurable workflow impact.
AI transformation | Analytics engineering | Data platforms
Byron Fung
I help companies turn complex business operations into scalable data, analytics, AI, and automation capabilities: trusted metrics, reliable platforms, practical workflows, and teams that can deliver them repeatedly.
Leadership Profile
Data, AI, and analytics systems that carry real business logic.
My work sits where analytics engineering, data engineering, product, operations, customer success, and executive decision-making meet. I focus on turning ambiguous operating problems into dependable technology capability: clear metric definitions, observable pipelines, tested transformations, AI-enabled workflows, and models that explain the business rather than merely expose tables.
I have built teams from early stage to scale, led globally distributed engineering and analytics groups, advised executive stakeholders, and established practices for governance, testing, documentation, observability, and AI-assisted development. The throughline is practical platform thinking: make the right thing reusable, governed, measurable, and easy for teams to adopt.
Scope
Where strategy, architecture, and execution connect.
Customer-facing solution architecture
Translating executive and customer requirements into scalable analytics, reporting, and platform designs for enterprise SaaS and complex operating environments.
Decision science and data products
Building pricing, compensation, forecasting, churn, LTV, clustering, quota, and territory models that support revenue operations and go-to-market decisions.
Operating models for scale
Establishing team structures, technical standards, governance, OKRs, documentation, and review practices that improve consistency across distributed teams.
Selected Work
Building foundations for product, platform, and customer outcomes.
Vice President, Analytics and Data Science
As the founding analytics and data hire at Forma.ai, I built and scaled a globally distributed analytics organization of 15 engineers supporting 30+ enterprise customers, with reusable data products for incentive compensation, sales performance, territory, quota, forecasting, and revenue operations workflows. The team covered a wide mandate, including customer delivery, data integration, BI reporting and machine learning models.
Data Engineer, Analytics Platform
I was a key member of the Data Hub team which was responsible for migrating the legacy data warehouse to Databricks. I developed Python, Spark, and Databricks pipelines for large-scale retail and loyalty datasets, built a Metrics Factory semantic layer, and tuned distributed workloads for repeatable partner analytics and production reporting applications.
Data Analytics Lead
I was the founding Analytics team member at Rubikoud, where I partnered with enterprise retail customers and internal product, data science, and engineering teams to operationalize machine learning outputs for promotion effectiveness, pricing, forecasting, merchandising, and decision-support workflows.
How I Work
A platform mindset for analytics teams.
Strong analytics engineering is not only a stack choice. It is the operating system for how teams define, change, verify, automate, and reuse business logic.
01
Semantic modeling and governed metrics
Reusable KPI definitions, fact and dimension models, star schemas, and clear ownership.
02
Reliable lakehouse and cloud data platforms
Databricks, Spark, Python, SQL, Fivetran, AWS, pipeline quality, observability, and performance tuning.
03
AI-assisted engineering and adoption
OpenAI Codex, GitHub Copilot, ChatGPT, Claude, prompt design, workflow automation, validation, and review practices.
04
Executive and customer advisory
Cross-functional delivery across product, engineering, operations, customer success, and executive stakeholders.
Resume
Experience, education, and certifications.
Background
Master of Management Analytics from Queen's University
Bachelor of Applied Science in Industrial Engineering from the University of Toronto
Certifications
Certified Analytics Professional (CAP-Expert)
SAS Certified Predictive Modeler
Technical Focus
Databricks, Spark, Python, SQL, Fivetran, dbt, semantic layers, modern ELT, data quality, observability, AI-assisted development, and workflow automation