Remote Data Scientist: Time Series Forecasting for Energy

Jobgether; Netherlands; Teletrabalho; EUR 70 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Fully Remote Work

International Collaboration

Meaningful Technical Impact

Resumo da oferta

Jobgether, on behalf of a partner company, is seeking a Data Scientist (Time Series Forecasting) based in the Netherlands to join a data-driven team powering a live energy trading platform.

You will build and optimize time series models for weather conditions, energy market prices, and electricity grid supply and demand, translating forecasting into robust, production-ready code within a fully remote, distributed environment.

Qualificações

• Bachelor's degree or higher in a quantitative field.
• At least three years of relevant experience in data science or forecasting.
• Experience with time series forecasting and practical model deployment.
• Proficiency in Python and SQL; Go is a plus.
• Excellent English communication in a remote, international setting.

Responsabilidades

• Design, develop, and refine forecasting models for weather, energy prices, and grid supply-demand.
• Translate algorithms into robust, production-ready code integrated with a live trading platform.
• Analyze data, identify patterns, and improve forecast accuracy for trading decisions.
• Incorporate AI-assisted coding tools to speed up development.
• Collaborate with distributed teams to align models with business needs.

Conhecimentos

Time Series Forecasting

Data Science

English communication

Analytical thinking

Problem solving

Hands-on coding

Formação académica

Bachelor's degree or higher in Mathematics / Econometrics / Physics / Engineering

Ferramentas

Python

SQL

Go

Descrição da oferta de emprego

Jobgether, on behalf of a partner company, is seeking a Data Scientist (Time Series Forecasting) based in the Netherlands to join a data-driven team powering a live energy trading platform.

You will build and optimize time series models for weather conditions, energy market prices, and electricity grid supply and demand, translating forecasting into robust, production-ready code within a fully remote, distributed environment.