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Sr. Quantitative Meteorologist

Job in Bloomington, Hennepin County, Minnesota, USA
Listing for: Selby Jennings
Full Time position
Listed on 2026-05-31
Job specializations:
  • Business
    Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Sr. Quantitative Meteorologist (PR/592311) Houston, Minnesota

Salary: USD
175000 - USD
225000 per year + Performance Bonus

Summary

A leading, global energy trading organization is seeking a Sr. Quantitative Meteorologist to support its North American power and gas markets. This role sits within a front‑office trading analytics team, partnering directly with the Head of Power Trading to deliver actionable weather insights across short, medium, and seasonal horizons. The position blends advanced forecasting, data science, and market impact analysis in a fast‑paced environment.

Key Responsibilities

  • Analyze global and regional weather models to forecast variables impacting US energy markets across multiple time frames (short‑term through seasonal).
  • Provide real‑time support and daily briefings to trading and portfolio management teams, with focus on ERCOT, CAISO, and PJM.
  • Produce regular reports on weather‑driven market risks and opportunities across North America.
  • Collaborate with quantitative and technology teams to build and enhance internal tools and data pipelines for weather analytics.
  • Contribute to development of forecasting frameworks, model improvements, and forward‑looking research.
  • Partner with global teams to align on broader weather and climate perspectives.
  • Lead or contribute to data science initiatives combining large‑scale weather and energy datasets.

Requirements

  • Advanced degree (PhD or Master’s) in Meteorology, Atmospheric Sciences, Physics, or a related discipline.
  • 5+ years of experience in energy meteorology within a trading or commercial environment.
  • Strong expertise in numerical weather prediction models and their comparative strengths/limitations.
  • Advanced programming skills in Python.
  • Solid understanding of weather impacts on US power and gas markets.
  • Excellent communication skills with the ability to translate complex analysis into clear, actionable insights.
  • Familiarity with machine learning techniques is a plus.
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