Company Description

MIR Insight forecasts demand and price developments in the materials industry, enabling companies to reduce waste and minimize losses. We are a fast-growing tech startup serving leading industry players such as K.D. Feddersen, Maral Overseas Ltd, and Jobachem, supported by international investors. Our goal is to provide our users with innovative, reliable, and user-friendly software. Join us on our mission to transform the manufacturing supply chain into a highly efficient, sustainable, and near-predictive economy.

Your Mission

Design, build, and maintain machine learning pipelines that turn chaotic real-world data into reliable, actionable forecasts. You’ll be at the core of MIR’s forecasting engine, working closely with our CDO, data analysts, and customers to continuously improve the accuracy, robustness, and scalability of our forecasting stack.

What You’ll Do

• Develop and improve machine learning models for time series forecasting (supply, demand, prices)
• Evaluate and optimize model performance across sectors, geographies, and time horizons
• Automate model retraining, validation, and deployment within our production environment
• Select and integrate high-impact data sources (market, climate, macroeconomic, etc.)
• Design experiments to test model assumptions and forecast stability under uncertainty
• Collaborate with analysts and customers to interpret results and align with business goals
• Document forecasting logic and results in a reproducible, scalable format
• Stay on top of emerging research in forecasting, ML, and decision intelligence
• Contribute to the architecture of our internal forecasting library and APIs

What We’re Looking For

• 3–6 years of experience in ML engineering, data science, or applied forecasting
• Deep knowledge of time series forecasting techniques (statistical, ML, hybrid)
• Proficient in Python and common ML/data tools (Pandas, scikit-learn, XGBoost, PyTorch, etc.)
• Experience building robust ML pipelines (training, validation, monitoring, deployment)
• Strong understanding of model diagnostics, error metrics, and production reliability
• Fluent in English; excellent technical communication skills
• Bonus: experience with causal inference, probabilistic forecasting, or scenario modelling
• Bonus: prior work with industrial, supply chain, or commodity data

What We Offer

• A rare chance to build the forecasting engine of the future from the ground up
• Significant technical ownership and fast decision-making
• Competitive salary and equity in a fast-growing venture
• On-site but with flexibility (Porto HQ )
• Mentorship from experienced founders and domain experts
• Career growth into technical leadership or research-heavy specialization

💡 At MIR Insight, we believe that better forecasting can save millions in waste and gigatons in emissions. If you want to make AI matter—in the real economy—come build it with us.