Quant Machine Learning Engineer - Market Signals & Forecasting

About the role

Carbon Insights is seeking a Quant Machine Learning Engineer to own and operate its production suite of market‑signal indicators and EU power forecasting models. You will design, validate, and run classification and regime‑detection models that generate real‑time signals for carbon and energy markets.

Key responsibilities

• Develop and maintain intraday and multi‑month price‑direction signals, COT‑based weekly signals, and regime indicators.
• Build, retrain, and serve weather‑driven generation and demand models for EU power markets.
• Engineer data pipelines that ingest market, auction, COT, fundamentals, and weather data; create features; train models; and schedule inference.
• Deploy models and pipelines on AWS (Lambda, Step Functions, ECR) using CI/CD, and ensure robust monitoring, alerting, and data‑quality checks.
• Maintain reproducible training workflows, thorough back‑testing (walk‑forward, no leakage), and clear documentation.

Required profile

• Strong Python and machine‑learning fundamentals, demonstrated through production work or solid projects.
• Deep understanding of time‑series and classification modeling, feature engineering, and rigorous validation.
• Ability to quickly learn or already know AWS services, Docker, Git/CI‑CD, and SQL/PostgreSQL.
• Bias toward reproducibility, testing, documentation, and ownership of production systems.

Required skills

• Python, pandas, numpy, scikit‑learn
• XGBoost or LightGBM (optional but a plus)
• Time‑series and classification modeling
• AWS Lambda, Step Functions, S3, ECR
• Docker
• Git and CI/CD pipelines
• SQL / PostgreSQL (Supabase experience a plus)