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JAMES NORDLUND

SENIOR LEADER, SCIENCE AND MLE
| linkedin.com/in/jamesnordlund | github.com/jamesnordlund

;; ABOUT

Senior leader with extensive experience leading applied science initiatives at scale. Expert in building high-performing teams, driving data-driven decision making, and delivering transformative AI/ML solutions that impact millions of users.

;; PROFESSIONAL EXPERIENCE

Head of Applied Science and MLE (Worldwide Sustainability Science and Innovation) Amazon 2026 - Present
  • Lead an organization of applied scientists and machine learning engineers
  • Developed physical AI systems for materials science
  • Created agentic systems for third-party clients
Head of Causal and Forecasting Science (Worldwide Pricing and Promotions) Amazon 2024 - 2026
  • Set long-term business vision for cross-functional projects that span product, science, and engineering
  • Architected and executed ML strategy for $10B+ sized businesses
  • Mentored science leaders and established best practices
Senior Economist, Technical Lead (Worldwide Pricing and Promotions) Amazon 2022 - 2024
  • Defined new distributional pricing theory for improved business logic under uncertainty, shifting the multi-year roadmap for 30+ scientists
  • Designed SOTA algorithms for causal matching in high-dimensional spaces on big data
  • Created causal forecasting models for heterogeneous intertemporal effects
Director of FinTech Innovations Lab LSU 2017 - 2022
  • Oversaw international recruiting of Ph.D. students and advised doctoral research projects
  • Designed, built, and administered a local compute server for JupyterHub and RStudio
  • Developed data-driven insights using topic modeling, spectral clustering, and NLP
Research Scientist and Technical Lead Texas A&M University 2011 - 2017
  • Owned the migration of existing research resources to a new HPC cluster
  • Developed statistical/mathematical models in R, Python, Stata, SAS, and Matlab

;; TECHNICAL EXPERTISE

Languages: Python, R, SAS, SQL, Stata, Scala
ML/AI: EC2, EMR, PyTorch, Sagemaker, Scikit-learn, XGBoost, Spark MLlib
Infrastructure: AWS, GCP, Docker, Airflow, MLflow
Data: Spark, Redshift
Tools: Git, Jupyter, Linux, CI/CD

;; EDUCATION

Ph.D. in Financial Economics Texas A&M University
B.A. in Mathematics Trinity University
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