Extensive experience in developing and implementing machine learning, Deep Learning, NLP models across various domains. Proven ability to guide and lead the development of complex models, ensuring accuracy, scalability, and performance.
Strong proficiency in Python, including relevant libraries and frameworks for machine learning, such as scikit-learn, XGBoost and Keras. Ability to write efficient, clean, and scalable code for model development and evaluation.
Proven experience in enhancing model accuracy through engineering techniques, such as feature engineering, feature selection, and data augmentation. Ability to analyze model samples in relation to model scores, identify patterns, and iteratively refine models for improved performance.
Strong expertise in deploying machine learning models to production systems. Familiarity with the end-to-end process of model deployment, including data preprocessing, model training, optimization, and integration into production environments.
Experience in project delivering Weibull distribution, Gaussian Distribution etc..
Domain : Manufacturing
Primary Skills
Experience with Machine Learning Model Development
Expert Level Proficiency in Data Handling (SQL)
Python Programming
Model Engineering and Improvement
Model Deployment and Productionlization
Secondary Skills
Experience with Cloud Computing: Proficiency in utilizing the Cloud Web Service (AWS) cloud computing platforms. Experience in using Cloud ML services such as Sagemaker, Azure ML, GCP Vertex etc.