Experienced builder, open to the right next opportunity
Over the last decade I have worked across forecasting, pricing, recommendation, and operational ML in production settings. I am now looking for the next chapter: strong teams, meaningful problems, and opportunities where hands-on technical judgment still matters.
Why teams bring me in
I am an applied machine learning builder with a hands-on background in forecasting, pricing, recommendation systems, and production data products. Most of my work has lived in environments where reliability, clarity, and operational usefulness matter more than hype.
I enjoy turning ambiguous business problems into systems that actually ship. That can mean designing a grounded LLM workflow, improving an existing model stack, building better evaluation loops, or helping a team move from prototype thinking to dependable production behavior.
Right now I am especially interested in the next role or collaboration where I can contribute as a senior builder: close to the work, close to the stakeholders, and focused on useful outcomes.
Scaled network forecasting
Built forecasting systems that could survive constant network change, new locations, new product launches, and noisy operational data.
Made pricing models more usable
Focused on practical model design, latency, interpretability, and business continuity in environments where downtime is expensive.
Led through ambiguity
Strong projects need more than model quality; they need communication, trust, and systems people can operate.
Where I add value
Turn fuzzy ideas into scoped, useful products and decision engines, with clear user value, realistic architecture, and a path to delivery.
Design grounded assistants, retrieval workflows, internal knowledge tools, and evaluation loops with an eye on trust, cost, and maintainability.
Build or improve forecasting, pricing, recommendation, scoring, and optimization systems with an emphasis on measurable business impact.
Bring senior technical judgment, mentoring, prioritization, and cross-functional translation without drifting away from hands-on execution.
Core expertise
Retrieval-augmented generation, prompt workflows, source-grounded answers, evaluation loops, and internal copilots.
Forecasting, regression, classification, recommendation, anomaly detection, and experimentation in real operating environments.
Pricing services, operational planning tools, automation pipelines, and data products that have to support live business decisions.
Bridging product, engineering, operators, analysts, and leadership so complex systems stay usable, trusted, and aligned with the business.
Ways I can contribute
A strong fit if you need someone who can own messy ML and AI problems end to end while collaborating well across product, engineering, and operations.
Useful for teams that want a pragmatic builder who can shape direction, mentor others, and still stay close to the code and systems.
Available for focused advisory or build engagements when the problem is a strong fit and the work is meaningful.
Open to new opportunities