Opis
Tired of building yet another chatbot POC? Do you want to train ML models that bring real monetary value and run at a billion-scale? Do you feel like introducing a brand-new probabilistic methodology for a real-world problem?
We build the AI-powered operating system for healthcare marketing - programmatic advertising, data intelligence, patient affordability and AI-enabled engagement for the life sciences industry. We are looking for a person who knows how to design and implement statistical methods to extract signals from large, messy, real-world datasets and use them for prediction. Everything we build on top of that, from audience reach to specialty insight to measurement, is only as good as your layer.
Your tasks Measuring existing model performance and finding ways to improve it Owning the design of the new methodology and training the next-gen model for increased predictive power, sample efficiency, and scalability to large datasets Extracting unique entities and sparse attributes from heterogeneous sources – both structured and unstructured Designing and implementing probabilistic entity linking & matching across multiple large healthcare datasets Exploring graph technologies and graph theory Building and owning an analytics data store, evaluation, and monitoring pipelines
Requirements
Minimum 5 years of experience in training and monitoring ML models for production use Experience with data and ML engineering, including ML-facing ETL processes over very large datasets
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