Meteorological Data Scientist

ZipRecruiter; Berlin; Vor Ort; EUR 55.000 - 85.000; Vollzeit

Zusammenfassung

A leading company in energy trading is seeking a Meteorological Data Scientist / Quantitative Analyst to join their computational team. This role involves developing analytical models and optimizing data pipelines to provide insights for renewable energy forecasting and market strategies. Candidates should have a strong background in data science and meteorology, proficient in R and familiar with energy market data.

Qualifikationen

• Experience with end-to-end data pipelines and data ingestion.
• Strong proficiency in R (tidyverse, data.table, modeling packages).
• Experience in low-latency application design.

Aufgaben

• Develop and maintain statistical and machine learning models.
• Build and optimize ETL pipelines for data.
• Transform large datasets into actionable insights.

Kenntnisse

Data ingestion

Feature engineering

Statistical modeling

Machine learning

Data wrangling

Automation

High-performance coding

Effective communication

Ausbildung

Background in meteorology, climate science, or spatial data analysis

Tools

R

Python

Jobbeschreibung

Job Description

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
• 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