Data Scientist (Time Series Forecasting)

Role Overview

Accountabilities

• Time Series Forecasting: Design, develop, and refine forecasting models for weather conditions, energy market prices, and electricity grid supply and demand.
• Production Model Development: Translate forecasting algorithms and analytical models into robust, scalable, production-ready code that powers a live energy trading platform.
• Data Analysis & Model Optimization: Analyze datasets, identify patterns and trends, and improve forecasting accuracy to support trading decisions.
• AI-Assisted Development: Incorporate agentic coding tools into daily development workflows to accelerate implementation and productivity.
• Technical Integration: Work with data pipelines, analytical systems, and production environments to ensure forecasting solutions are reliable and maintainable.
• Cross-Functional Collaboration: Communicate technical findings, explain forecasting approaches, and collaborate with distributed teams to align model development with business requirements.

Requirements

• Bachelor's degree or higher in Mathematics, Econometrics, Physics, Engineering, or another closely related quantitative discipline.
• At least three years of relevant professional experience in data science, quantitative analysis, forecasting, or a related field.
• Demonstrated experience developing and applying time series forecasting models.
• Strong proficiency in Python and SQL for data analysis, model development, and production implementation.
• Experience with Go is considered an advantage.
• Regular, hands-on use of agentic coding tools as part of your daily development workflow.
• Excellent English communication skills for a remote, international environment.
• Strong quantitative reasoning, attention to detail, and a practical approach to complex forecasting challenges.
• Experience working with energy markets, electricity trading, power grid data, or weather datasets is a plus.

Benefits

• Fully remote work from anywhere in a distributed team environment.
• International collaboration on a global energy trading platform.
• Meaningful technical impact on real-world energy market decisions.
• Advanced data science challenges in time series forecasting.
• Modern development practices using agentic coding tools.
• Professional growth in quantitative modeling and production-grade data science.

How Jobgether Works

• This position is listed on behalf of a partner company, which manages all applications and next steps.
• Jobgether uses an AI-powered matching process to review applications against the role's core requirements and shares a shortlist with the hiring company.
• Final decisions and next steps are managed by the hiring company's internal team.