Doruk Cengiz

Doruk Cengiz

Data Science / AI Lead

UMASS Amherst

Biography

Hi, I am a senior research fellow at UMass Amherst. Previously, I was a lead data scientist at The Home Depot and a data scientist at OMP, where I worked on producing GenAI chatbots for internal users, personalized price recommendations, and supply chain forecasting.

I have received a Ph.D. in Economics and a M.S. in Statistics from the University of Massachusetts Amherst.

Interests
  • GenAI/LLM
  • Machine/Statistical Learning
  • Causal Inference & Econometrics
  • Forecasting
  • Labor Economics
Education
  • PhD in Economics, 2019

    University of Massachusetts, Amherst

  • MS in Statistics, 2016

    University of Massachusetts, Amherst

  • BA in Economics, 2012

    Bogazici University

Experience

 
 
 
 
 
Senior Research Fellow
Mar 2025 – Present Raleigh, NC

Responsibilities include:

  • Conducting research on the evolution of methodological and topical trends in industrial organization and agricultural economics over the last five decades
  • Develop Big Data and AI infrastructure to support scalable analysis
 
 
 
 
 
Lead Data Scientist
Jan 2022 – Jan 2025 Atlanta, GA

Responsibilities include:

  • Led development of an internal sales assistant chatbot, resulting in an estimated ~5% gain in labor productivity.
  • Transforming high volume data into actionable business information
  • Developing demand models to determine optimum price levels that maximize Home Depot’s market share without decreasing the gross margin
 
 
 
 
 
Data Scientist
Aug 2019 – Jan 2022 Atlanta, GA

Responsibilities include:

  • Implementing frontier forecasting methods on big data sets to improve forecast accuracy
  • Coaching and onboarding junior data scientists and data science/consultants
  • Tidying “untidy” data, creating visualizations, and presenting results to technical and non-technical audience (e.g. other team members, customers, consultants)
 
 
 
 
 
Researcher / Graduate Research Assistant
May 2015 – Aug 2019 Amherst, MA
Researched on cutting edge predictive and causal machine learning, statistical, and economic models to explain and forecast supply and demand movements in markets.