Data Scientist (m/f/d)

Stellenbeschreibung:

Join to apply for the Data Scientist (m/f/d) role at Bees & Bears GmbH

You don’t want an ordinary job. You want to build something that truly matters. Be part of shaping it from day one, move fast and feel your impact. In a startup that doesn’t ask if something is possible – but how fast. Then you’ve come to the right place!

At Bees & Bears, we’re a Climate FinTech on a mission to unlock capital for the energy transition. We believe finance is the key to accelerating the shift toward a sustainable future. The challenge ahead is massive: by 2050, the world needs to invest €150 trillion (!) to reach climate neutrality. 65% of this investment will need to be financed through loans.

Our mission is to channel capital into the sustainable economy — to accelerate the transition and make the world greener

What we do:

We work closely with installers of climate hardware such as solar systems, energy storage, and heat pumps — enabling their customers to finance installations easily through monthly installments. Our platform provides the technical and financial foundation to make this happen. In doing so, we’re actively accelerating the energy transition — for households, for our partners, and for the planet.

We’ve recently secured €500 million in funding commitments to green 25,000 households over the next two years. Prior to that, we raised two funding rounds backed by several renowned VCs — and we’ve been growing rapidly ever since.

Tasks

Design & build the core ETL/ELT pipelines (Python/Django) that power all credit decisioning and risk monitoring processes, ensuring >95% data availability and reliability within the first 6 months.
Integrate the Loan Management System (LMS): Lead the technical data mapping, ingestion, and transformation setup to ensure smooth, accurate data flow into the risk data environment.
Automate risk & portfolio reporting by replacing manual exports with fully automated pipelines delivering data into Google Sheets and Excel for the Risk and Finance teams.
Establish a data quality framework including validations, monitoring, and alerting to ensure accuracy, completeness, and consistency of underwriting and regulatory datasets.
Enable scalable risk models by preparing clean, structured, and timely datasets for B2B/B2C scoring, forecasting, and risk‑based pricing models.
Optimize system & query performance through regular audits of ETL workflows, SQL queries, and data storage to improve loading times and reporting speed.
Collaborate closely with Risk, Finance, Engineering, and Product to ensure data infrastructure supports business growth and regulatory requirements.

Your profile

5+ years of experience as a Data Engineer / ETL Developer, with a strong track record building scalable, production‑grade data pipelines
Strong Python skills for data processing; Django experience highly desirable
Advanced SQL expertise including query optimization and handling large datasets (*)
Experience automating data flows into Google Sheets, Excel, or BI tools; familiarity with Tableau, Looker, or similar is a plus.
Hands‑on, pragmatic problem‑solver with strong ownership and a commitment to high data quality (*).
Experience with financial or credit‑risk data, reporting, or LMS systems is a strong advantage.
Excellent English skills; German is a plus

What we offer:

Guaranteed impact: Every deal your team closes contributes directly to the energy transition and saves at least dozens of tons of CO₂ emissions.
27 days of paid vacation and unlimited time off for climate activism and demonstrations.
Keep learning — continuously explore the latest climate tech developments, from cutting‑edge energy storage solutions to innovative recycling methods or heat recovery from wastewater.
No progress without mistakes. We encourage you to try things out, take ownership, and get hands‑on insights across all areas of the startup.
By day, we’re driving the green transformation — but we make sure to have fun along the way. We’re a close‑knit, dynamic team that enjoys regular events and post‑work “Bees & Beers” hangouts.