Description: * Responsible for hypothesis testing, predictive model validation, and model explainability (SHAP, LIME). * Must master Machine Learning and Deep Learning algorithms, with hands-on experience in building and tuning models. * Experience with Python (PEPs, libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch); * API development (FastAPI, Flask) and integration with LLMs (e.g., GPT). * Proficiency in Databricks, SQL, and GIT is essential, along with a track record of model deployment projects, AI agents, and intelligent APIs. * Hypothesis testing * Predictive model validation * Model evaluation metrics and explainability (SHAP, LIME, etc.) Machine Learning & Deep Learning: * Mastery of key supervised and unsupervised algorithms * Practical experience in building, evaluating, and tuning models * Python development: 2512200202551360488