Read and translate the latest research (e.g., arXiv papers) into production-ready solutions in Python.
Prototype and iterate on machine learning models, focusing on areas such as regression, causal inference, optimization, and vector embeddings.
Collaborate with cross-functional teams to embed ML and AI capabilities directly into our software platform.
Partner with data scientists to design experiments and apply statistical concepts to real-world data.
Optimize, test, and scale ML models to support mission-critical healthcare analytics.

Requirements

Strong experience implementing ML models in Python.
Familiarity with regression, embeddings, causal inference, and optimization techniques.
Experience applying statistical methods to exploratory data analysis.
Comfort working with modern ML libraries and frameworks.
Bonus points if you have worked with NLP tasks (LLMs, spaCy, neural networks).
Bonus points if you have experience with recommender systems, latent factors, matrix factorization.
Bonus points if you have knowledge of graph algorithms.

Benefits

retirement benefits
health and welfare benefits
paid time off
parental leave
life and accident insurance
other voluntary and well-being benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythonmachine learningregressioncausal inferenceoptimizationvector embeddingsstatistical methodsexploratory data analysisnatural language processinggraph algorithms

Soft Skills

collaborationcommunication