DataRobot is based around delivering best-in-class data science solutions and this position provides the opportunity to build key data science components of our system.
The Explainable AI team is pioneering the AutoML industry by inventing cutting edge solutions to optimize AI explainability and interpretability.
As machine learning capabilities mature and automation increases, there will always be a need for humans to understand and explain the behavior of AI systems.
You will play a key role in realizing this vision by actively contributing to the development of our automated insights toolchain.
We are looking for talented people with deep knowledge of Machine Learning / Statistics and strong engineering skills. Your responsibilities will include the automation of data science best practices, building tools to address data quality issues and developing state-of-the-art insights.
Integrate leading open source solutions and build in-house solutions to explain the output of any machine learning model
Automate interesting and actionable insights from data
Design and build solutions to integrate domain knowledge into the modeling process
Contribute to a transparent and accurate documentation of the inner workings of models
Recommended background : 5+ years of combined Python engineering and machine learning experience
Experience writing maintainable, testable, production-grade Python code
Understanding of different machine learning algorithm families and their tradeoffs (linear, tree-based, kernel-based, neural networks, unsupervised algorithms, etc.)
Good command of scientific Python toolkit (numpy, scipy, pandas, scikit-learn)
Understanding of time, RAM, and I / O scalability aspects of data science applications (e.g. CPU and GPU acceleration, operations on sparse arrays, model serialization and caching)
Software design and peer code review skills
Experience with automated testing and test-driven development in Python
Experience with Git + GitHub
Comfortable with Linux-based operating systems
Deep knowledge of data science best practices
Strong intuition of models strength and weaknesses
Competitive machine learning experience (e.g. Kaggle)
Knowledge of the model validation / approval process in a regulated environment (US / EU / APAC)
Previous experience of deploying and maintaining machine learning models in production
Individuals seeking employment at DataRobot are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.