ESG Data Scientist (all genders) | carbmee
Intro
This is a modeling and applied ML role grounded in a very specific, very real domain problem: when a customer's data is missing a key field, you're the one who understands why that forces a fallback from activity-based to spend-based emissions estimation, and you're the one building the models that make that fallback as accurate as possible rather than a rough guess.
Your tasks
- Develop and fine-tune machine learning models and LLM-based workflows to improve emissions data coverage, accuracy, and inference at scale: including estimation logic for incomplete supplier or product data.
- Build the logic layer that handles real-world data gaps: missing weights, inconsistent units, unmapped commodities, and other patterns that show up constantly in customer ERP exports.
- Work with LLM-assisted data mapping (we use Claude extensively) and build the validation and guardrail logic that catches hallucinated mappings before they reach a customer's numbers.
- Design and evaluate models against the GHG Protocol scope structure: including the Scope 3.1/3.4 split underlying Supply Chain Carbon Footprint (so that model outputs are not just statistically sound but methodologically correct).
- Analyze model performance across customer deployments and iterate quickly; a model that works for one industrial sector's data patterns often needs real rework for another.
- Translate model outputs and confidence levels into language that customer sustainability and technical teams can trust and act on.
- Partner with product engineering to bring successful modeling approaches into the core EIS™ platform.
Your profile
Associate: you have a strong quantitative background (statistics, applied ML, or data science) with some hands-on model-building experience (academic, internship, or early career) and real curiosity about the sustainability/carbon accounting domain.
Senior: you have a proven track record shipping ML models into production (not just notebooks), ideally including work with incomplete or noisy real-world data, and are comfortable owning modeling decisions with significant downstream business impact.
- Strong Python skills and solid grounding in statistics and applied machine learning; SQL proficiency for working with real enterprise data.
- Experience with LLM-based workflows and prompt/pipeline design is a strong plus.
- Comfort with ambiguous, incomplete data: and the instinct to flag a limitation rather than silently smooth over it.
- Familiarity with GHG Protocol or carbon accounting concepts; genuine willingness to build deep domain fluency is required.
- Ability to communicate modeling tradeoffs clearly to both engineers and non-technical business stakeholders.
- Degree in Data Science, Statistics, Computer Science, or a related quantitative field, or equivalent practical experience.
- Fluent in English and German.
- Based in Munich.
Benefits
- Unique & Powerful Mission: join a fast-growing and ambitious tech company that is shaping the future of carbon management and fighting climate change
- Compensation & Rewards: a steep learning curve and ownership from day one. We offer an attractive compensation package, including virtual stock options
- Health & Wellbeing: Urban Sports Club subscription to stay healthy & fit.1:1 coaching sessions with Nilohealth for your mental well-being.
- Flexibility & Work-Life Balance: a flexible hybrid working culture with a lovely accessible office in Berlin-Mitte or the center of Munich
- Team Culture: Our transparency, Humility, and Accountability values create a unique and supportive working environment. Be part of a multinational, motivated team that thinks work should be fun!
- Connection & Networking: Summer Offsite, Winter Party, and regular team events We give you plenty of opportunities to connect with people, strengthen cross-functional relationships, and boost collaboration
- Trust & Transparency: monthly All-Hands Meetings, weekly update newsletters, and Founders Q&As. We keep you informed on current company numbers and goals
About us
carbmee is an Enterprise Software company built for the architectural backbone of the global economy. In an era where sustainability defines a company’s right to operate, we provide the System of Action for the world’s most complex manufacturing sectors with a strong footprint in Automotive and Defense.
We specialize in high-stakes, large-scale enterprise deployments where environmental data is no longer just a reporting requirement, but a critical strategic asset. Our platform empowers global industry leaders to transform fragmented data points into actionable intelligence, enabling them to make the defining decisions for the future of their products and supply chains.
At the heart of carbmee is a team of world-class talent: a powerhouse of engineers, industry experts, and visionaries dedicated to solving the most pressing industrial challenges of our time. We believe that solving the "hard-to-abate" problem requires the best minds in the world, and we are constantly looking for exceptional individuals to join our mission. We are calling this the "Industry Endgame".
Backed by a €20M Series A from top-tier investors and operating out of our hubs in Berlin and Munich, we are scaling rapidly, having the ambition to build a generational software company out of Germany.
