The business provides instant property intelligence for buildings across America and Europe by leveraging geospatial imagery, Computer Vision, and Machine Learning to instantly and automatically extract this proprietary data. They allow insurers and property stakeholders to access invaluable property information at record speed, which was first had to be done with on-site inspection. Due to the true innovation of their product, they are backed by a number of leading venture firms and insurers.
The teams work with geospatial data at scale, applying machine learning to solve real problems. As a senior data scientist, you’ll work together with computer Vision/Machine Learning Engineers, Data Engineers, Software Engineers, Product, and Sales teams to build robust, scalable machine learning models for identification and annotation of the built world and developing cutting-edge data science algorithms, e.g., using deep learning. You will develop expertise in ground truth generation, model performance analysis, iterative model development, and unsupervised mapping of the feature space to bring scientific rigor, scalability, and robust performance to their core product offerings. You will ideate and implement data-driven methodologies to help scale model performance across geographical, climatic, and temporal dimensions. One of the other focus areas is to contribute to design and automation of model training, model post-processing and evaluation pipelines at scale.
The company leverages all available tools and technologies to build a best-in-class tech stack, which affords them the flexibility of fast deployments, along with the stability to support aggressive SLAs for critical-path client APIs and applications. They build their models using Pytorch and Tensorflow, and leverage Python, Spark and Postgres across their AWS-deployed cloud infrastructure.
– A PhD in STEM field with 3 years hands-on working experience/ MSc with 5 years working experience
– Solid knowledge of statistical techniques, including hypothesis testing, statistical sampling, significance testing, statistical inference, maximum likelihood estimation, and experimental design, among others.
– Mastery of, supervised and unsupervised algorithms and their implementations, machine learning concepts including regularization, learning curves, optimizing hyperparameters, cross-validation, among others.
– Developing cutting-edge data science algorithms, e.g., using deep learning
–Advanced knowledge and significant programming experience in Python programming or other scripting language including relevant libraries like numpy, pandas, SciPy, matplotlib
– Familiarity with the Linux environment including shell scripting, Git and tools for reproducibility (e.g. virtual environments, Docker).
– Demonstrated expertise in building data tools for ETL and data analysis.
– Experience in building meaningful data visualizations using at least one scripting-based visualization tool such as matplotlib, d3.js or bokeh.
– Fluent English
– Salary based on experience and goes up until 100k
– Stock options package on top
– The office in Europe is in Munich and if you live in Germany, you can work 100% remote. Some office visits would be helpful, but you can decide this yourself.
– Working in openminded and intelligent environment
– Working in multidisciplinary teams consisting of data scientists, machine learning engineers, productowners and engineers.
If you would like to hear more, please let me know and we can arrange a convenient time to speak. A CV with your experience would be nice to send over to us. I’m available at Richard.firstname.lastname@example.org or +4930 217 800 71. Below is also a link to my calendar where you’re welcome to book a convenient time for you directly. https://calendly.com/richard-straub
Looking forward to hearing from you!