5 years of hands-on industry data science experience, using typical machine learning and data science tools including pandas, mlflow, scikit-learn, gensim, nltk, and TensorFlow/PyTorch
Experience building production-grade machine learning deployments on AWS, Azure, or GCP including drift monitoring
Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience
Experience communicating and teaching technical concepts to non-technical and technical audiences alike
Passion for collaboration, life-long learning, and driving value through ML
[Preferred] Experience working with Apache Spark to process large-scale distributed datasets
[Preferred] Experience working with the Databricks platform