About Us:
Spatio Metrics is an all-in-one platform for design analysis and data visualization for architects who want to deliver high-impact buildings within project constraints.
Unlike approaches that require designers to maintain custom scripts or wrangle with excel and PowerBI, Spatio Metrics is easy to use and backed by industry best practices so that they can assess and communicate consistent, data-backed design metrics on every iteration of every project, no matter how tight their deadline.
Where You Fit In:
As Data Science & Machine Learning Engineer/Researcher, you’ll develop data science and machine learning models that study how building design is related to health outcomes in hospitals. Working directly with our co-founder/CTO, you’ll help shape the direction of an early-stage startup and work towards the goal of bringing AI and data-driven workflows accessible to noncoders. This role is funded as part of a National Science Foundation (NSF) SBIR grant.
This role is for Winter 2022, with a flexible schedule to be determined in advance.
What You’ll Do:
Research machine learning and data science systems. You’ll conduct a literature review to identify the most relevant and cutting-edge techniques for the task at hand.
Prototype, train, and refine models. You’ll work with multiple datasets: an architectural dataset with characteristics like privacy, natural daylight, and travel distances, and another of non-identified patient health outcome data like mortality rates and pain medicine requests.
Test and evaluate models. You’ll develop workflows to systematically assess each model’s efficacy and summarize your recommendations based on the findings.
Lay the groundwork for product integration. Working with our software development team, you’ll advise on opportunities and best practices for integrating ML models in future product development.
What We’re Looking For:
Masters or PhD (can be a current student) with advanced coursework in data science and machine learning
Demonstrated experience with ML frameworks (Tensorflow, Keras, Pytorch, or similar) and multiple ML algorithms (i.e. regression, classification, clustering, dimensionality reduction, neural networks, etc.)
Experience with Python
Ability to understand recent ML research papers and summarize findings for a non-technical audience
Located in and eligible to work in the United States
Flexible, team player -- you’ll be a core member of a small team!
Curiosity, staying up to date with the latest developments and willing to learn new technologies
Bonus Points
Track record of published research
Experience with causal inference
Experience or interest in architecture, design, simulation, or building performance
Experience or interest in computer vision
Experience with interactive data visualization and/or front-end development (React, javascript)
Experience with C#, Grasshopper, Revit API
How to Apply
If this sounds like you, send a cover letter, resume, and links to 2-3 relevant projects to careers@spatiometrics.com with the subject line “Data Science & Machine Learning Engineer/Researcher Application.” We’re looking forward to hearing from you!