Meteorological Data Scientist

Vitus Commodities; Berlin; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A dynamic energy market player, Vitus Commodities, seeks a Meteorological Data Scientist / Quantitative Analyst in Berlin. Join their computational meteorology team to innovate in energy trading through robust analytical models and utilize large-scale meteorological data for actionable insights. This role melds data science, meteorology, and market strategy.

Qualifikationen

• Experience with end-to-end data pipelines.
• Skill in developing and maintaining statistical or machine learning models.
• Proficiency in R and familiarity with meteorological data formats.

Aufgaben

• Develop statistical and machine learning models for energy forecasting.
• Build ETL pipelines for meteorological data.
• Collaborate within a technical team to support innovations in analytics.

Kenntnisse

Data ingestion

Preprocessing

Feature engineering

Statistical modeling

Machine learning

Data wrangling

Automation

Communication skills

Tools

R

Python

Jobbeschreibung

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
• 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