Data Scientist

Evaluate Machine Learning Models: Analyze and validate machine learning and computer vision models to ensure they meet performance standards. Develop Metrics: Design and implement metrics to measure the effectiveness and accuracy of models. Failure Analysis: Perform detailed failure analysis to understand model weaknesses and identify areas for improvement. Data Processing: Preprocess and clean large datasets to prepare them for modeling. Model Optimization: Optimize models for performance and scalability, applying state-of-the-art techniques. Collaborate: Work closely with cross-functional teams, including software engineers, product managers, and other Data Scientists, to integrate models into production. Documentation: Document processes, model performance, and analysis results.