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Predium, Munich-based, is building the AI analyst for real estate data to support ESG and value management decisions. The role focuses on developing and improving data-driven models, statistical and machine learning methods, and simulation techniques using customer data.
Collaboration with engineering and product teams is essential to translate business needs into scalable solutions. Ideal candidates bring hands-on experience in data science, Python, and data pipelines, plus English and German
This Full time on site position offers great opportunities for career growth.
Over the past three years, Predium has built the leading real estate intelligence platform for ESG and value management in the DACH region - with the strongest names in the industry as customers: asset managers, housing companies, banks.
Our customer base, our data, our credibility - that's valuable capital for the next step.
Investment, credit, and asset management decisions in real estate are still made in Excel, case by case.
We're now building the AI analyst that takes this work off people's hands - working directly on the customer's own data, scalable without adding headcount.
We're well-funded, and we're bringing AI into real estate.
As a Data Scientist at Predium, you will help develop and improve the data-driven models behind our platform.
You will use statistics, machine learning, and numerical methods to solve well-defined problems related to buildings, energy performance, and real-estate decarbonization.
Working closely with our engineering and product team, you will turn real-world data into reliable analytical, simulation, and machine-learning models that identify optimization opportunities for more sustainable buildings and help customers make informed investment decisions.
Bonus: Initial experience with optimization methods, LLM-based data extraction, or uncertainty and sensitivity analysis.
Familiarity with real estate, building physics, or energy systems.
Experience with tools for physical simulation or energy modeling.
Stage: \~40 people, well-funded, on the way to defining the category. Early enough that a lot still needs to be built. Yes, it's messy sometimes - that's the whole point. If you're looking for a job with a finished playbook, this isn't the right fit.