AI & Technology Executive

David (Dave) Farnham

VP of AI & Engineering at ClimateAi. I build AI and data-insight products that help you make better decisions. I also build the teams that ship them.

15+ years applying machine learning and climate science to energy systems, infrastructure, agriculture, and climate risk. Hands-on with the code.

Portrait of David (Dave) Farnham headshot.jpg Add to public/images/

About

From peer review to production

I'm Dave. I started in research: a PhD with Upmanu Lall at Columbia, then a postdoc with Ken Caldeira at Carnegie Science and Stanford. I studied how weather and climate shape energy and water systems. That work produced 50+ publications and conference contributions.

At ClimateAi I've gone from senior scientist to VP of AI & Engineering. I lead a 12-person team across data science, ML, software and geospatial engineering, product, and Earth science. I write code most weeks. I care about forecasts and analytics that drive real decisions, responsible AI, and teams that ship and stick around.

David (Dave) Farnham presenting to an audience speaking.jpg Add to public/images/
Presenting at the AMS Annual Meeting, 2025.
  • Applied AI / ML
  • Responsible AI & Model Governance
  • Probabilistic Forecasting & Optimization
  • Energy & Climate Risk Analytics
  • Technical Product Strategy
  • Enterprise Solutions & Technical Sales
  • Multidisciplinary Leadership
  • Full-Lifecycle Startup Leadership

Experience

Leadership & industry

Industry

2025 — Present San Francisco, CA (remote)

VP of AI & Engineering

ClimateAi

Promoted through four roles: Director of Data Science (2024–25), Lead Innovation Scientist (2023–24), Senior Innovation Scientist (2021–23).

  • Lead a 12-person team across data science, AI/ML, software and geospatial engineering, product, and Earth sciences. Hired nearly all of them — none have left.
  • Own technical strategy and R&D for forecasting and climate-risk products built on petabyte-scale geospatial data. Hands-on in architecture, modeling, and code.
  • Work enterprise and government deals from first call through delivery, including mid- and high-six-figure contracts.
  • Turned bespoke customer work into repeatable products, cutting delivery times from weeks to hours.

Research positions

2018 — 2021

Postdoctoral Research Scientist

Carnegie Science & Stanford University

  • Worked with Ken Caldeira on renewable-energy reliability, wind and solar variability, and weather-driven electricity demand.
2012 — 2018

Graduate Researcher

Columbia University

  • Worked with Upmanu Lall on climate and weather modeling for energy systems, water resources, and infrastructure risk.

Education

2018

Ph.D., Water Resources & Climate Risk Engineering

Columbia University

Dissertation on spatio-temporal patterns in high-dimensional climate and weather data.

2015

M.S., Water Resources & Climate Risk Engineering

Columbia University

2012

B.S., Civil Engineering

SUNY Buffalo

Summa Cum Laude · Honors College

2012

B.A., Mathematics

SUNY Buffalo

Summa Cum Laude · Honors College

Fellowships

2015

NSF / National Research Foundation of Korea EAPSI Fellowship

National Science Foundation

2012–2018

Integrated Graduate Education and Research Traineeship (IGERT)

National Science Foundation

Research

Selected publications

  1. The Substantial Role of Weather Data in Consumer Spending Prediction: A Robust Machine Learning Assessment

    Journal of Retailing and Consumer Services · 2026

  2. Assessing Power System Disruptions and Economic Impacts from Increasing Extreme Heat Events in Southeast Europe

    World Bank · 2024

  3. Geophysical Constraints on the Reliability of Solar and Wind Power Worldwide

    Nature Communications · 2021

  4. Meteorology and Climatology of Historical Weekly Wind and Solar Power Resource Droughts over Western North America in ERA5

    SN Applied Sciences · 2021

  5. Robust Adaptation to Multiscale Climate Variability

    Earth's Future · 2019

50+ publications and conference contributions, cited 1,300+ times.

Contact

Let’s talk

Happy to talk AI, forecasting, climate risk, or building technical teams. Email is the fastest way to reach me.