Vitus Commodities actively trades electricity and natural gas contracts in global markets. We are seeking a Meteorological Data Scientist / Quantitative Analyst to join our computational meteorology team to support energy trading operations. Job Description As a Meteorological Data Scientist / Quantitative Analyst, you will develop and maintain robust analytical models, transforming large-scale meteorological data into actionable insights for renewable energy forecasting and market strategy. This is a collaborative, fast-paced environment at the intersection of data science, meteorology, and energy markets. Key Responsibilities Develop and maintain statistical and machine learning models for energy forecasting and market analysis Build and optimize ETL pipelines for meteorological data ingestion, feature engineering, and storage Transform large and diverse datasets into actionable business insights Monitor, evaluate, and improve model performance and data reliability Design and write highly efficient, optimized code with a focus on minimizing latency and maximizing computational performance Contribute to the automation and reliability of our data and modeling infrastructure Collaborate effectively within a technical team and support innovation in analytics and modeling Qualifications Experience with end-to-end data pipelines: data ingestion, preprocessing, feature engineering, modeling, and outputting to storage (e.g., Parquet, databases). Demonstrated skill in developing and maintaining statistical or machine learning models (forecasting, regression, classification). Strong data wrangling and automation abilities Proven experience designing efficient, high-performance code for low-latency applications Effective communication skills and a collaborative, solution-oriented mindset Strong proficiency in R (tidyverse, data.table, modeling packages), and experience with meteorological data formats (GRIB, NetCDF) is highly preferred Experience with Python (pandas, xarray, pygrib, cfgrib) is advantageous Background in meteorology, climate science, or spatial data analysis is a plus Familiarity with energy market or trading data is a plus