This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist (Time Series Forecasting) based in Chile.

Join a data-driven team developing advanced forecasting solutions that power a live energy trading platform. In this role, you will build and optimize time series models to predict weather conditions, energy market prices, and electricity grid supply and demand. Your work will directly support data-informed trading decisions by transforming analytical models into reliable, production-ready code. You will collaborate in a fully remote, distributed environment where quantitative expertise, technical excellence, and practical problem-solving are highly valued. Leveraging Python, SQL, and modern AI-powered coding tools, you will help bridge the gap between sophisticated forecasting techniques and real-world business applications. This opportunity is idóneo for a hands-on data scientist who enjoys solving complex prediction challenges and delivering measurable impact in the evolving energy sector.

n





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 integrates with and powers a live energy trading platform.

• Data Analysis & Model Optimization: Analyze relevant datasets, identify patterns and trends, and improve forecasting accuracy to support reliable, data-driven trading decisions.

• AI-Assisted Development: Incorporate agentic coding tools into daily development workflows to accelerate implementation, improve productivity, and support efficient software development.

• Technical Integration: Work with data pipelines, analytical systems, and production environments to ensure forecasting solutions are reliable, maintaina

📌 Data Scientist (Chile)
🏢 Jobgether
📍 Chile