Data Scientist with ML experience
4 weeks ago
We are Building Atlas. Our vision is a fully sustainable commercial real estate sector. Our mission is to make this a reality through rapidly scaling building retrofits: the most sustainable building is the one that already exists. With a zero-touch approach, requiring nothing but the addresses of buildings, we help owners of commercial real estate portfolios: (1) find the best path to retrofitting their buildings; (2) avoid stranding risk and increase the value of their assets; (3) and get access to preferential financing and delivery partners to get the work done.
Our goal is to get as many buildings as possible retrofitted, so we recommend retrofit measures that bring the highest return on investment. Choosing the right building to focus on requires understanding its physics (building envelope and the energy systems), its current lease terms and use, its current value and future “green premium,” and the value of energy flexibility in a future grid. We gather all this data and build machine learning models to find the optimum retrofits across a portfolio of buildings.
To make this possible, we’re building a diverse team of people passionate about solving climate change in the built environment. We’re scattered around Europe and come from a variety of backgrounds, and we need your help
We’re looking for a creative data scientist / ML engineer who ideally has experience in the built environment. You’ll be passionate about finding insights from messy data, and working in a scrappy startup to drive our retrofit recommendations that will help customers reduce the carbon footprint of their buildings.
Tasks- Architect and implement data pipelines / ETL processes to support processing of data about buildings
- Find relevant insights across these multiple datasets
- Build algorithms and design experiments to merge and interrogate data
- Prototype retrofit recommendation models
- Collaborate with the engineering team to incorporate data science results into user-facing applications
- Work with customers to identify useful data insights that we can show in our platform
Minimum Qualifications:
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field
- 2+ years of professional experience in data science and analysis
- Competency in Python, R or other modelling languages, and Jupyter notebooks
- Experience building machine learning models
- Familiarity with database technologies (e.g., PostgreSQL, MySQL)
Preferred qualifications:
- Experience with geographic or urban datasets: addresses, building characteristics, energy, or GIS data
- Experience with Google Cloud data processing and analysis tools - Dataflow, BigQuery, Colab, Vertex AI
- Experience with enterprise SaaS development
- Experience working in a fast-growing startup environment
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