Verdigris is on a mission to sustain and enrich human life through responsive energy intelligence. Our AI sensors automate energy management and predict unseen equipment failures in mission-critical buildings. This is a critical step for autonomous, sustainable environments responsive to their inhabitants. Extraordinary outcomes need exceptional teams. As a company we value working together and continuously growing. About you As a Senior Data Scientist, your mission is to bring insights to life. You will build robust, scalable, and efficient algorithms for reducing the energy footprint of buildings across the globe. You are a team-minded data scientist who will refine our tech stack, our engineering culture, mentor other engineers and impact our portfolio of mission-critical commercial buildings. Your primary responsibility is to produce robust and meaningful insights and automations for our customers, but also help scale a growing team. Your communication skills will allow you to convey information to your team members, sales, marketing, and other teams. Required Qualification
- You hold an advanced degree (BS or MS) in Computer Science, Software Engineering, Computer Engineering, Mathematics, Physics or equivalent
- You learn continuously and are passionate about applying what you know about data science and ML in real-world applications such as reducing energy usage in buildings across the globe.
- You have at least 4 years of full time industry experience and are an expert in data science
- You have led and mentored engineering teams
- You have engineered a full release cycle of a commercial product
- You can code in 1 or more functional languages, Python, and Javascript.
- You embrace paired programming, test driven development and continuous integration
- You listen actively and build consensus
- You empathize strongly with customer problems
- You can communicate complex concepts simply
Nice to Haves
- You are experienced in our Machine Learning Stack (Pandas, Tensorflow, Keras, Numpy, Scikitlearn, Python, Scython, Pytorch)
- You are experienced in cloud computing environments like AWS, Docker, Kubernetes, Terraform.
- You understand SQL and relational database architectures and tradeoffs (PostgreSQL, MySQL, MSSQL, etc.)
- You’ve built and deployed production level machine learning and software at scale.