Worked on most of the in Data Science -Statistical, ML Architect, Deep Learning and Transformer, Generative AI, Prompt, LLM, Fine tune LLM,SOTA, Foundational Model, Multimodal, Diffusion model, Zero shot Learning, Few shot learning, NLP, Computer Vision, OCR, Time Series, A/B Testing, Search , Ranking and GNN • Certification in Data Scientist, ML Architect & Design, Deep Learning, Data Mining, Machine Learning Specialty, Azure ML Studio, AWS Sage Maker and GCP Vertex AI • Expertise in Data Collection, Data Cleaning, Web Scraping, Social Media API, Different Data Sampling, Data Label, Data Annotation and Data Augmentation • Expertise Feature Engineering like Feature Selection, Features Scaling, Feature Normalization, Feature Vectorize, Factor Analysis, Dimensionality Reduction, Regularization and Gradient Boosting • Created Data visualization and Story telling using PowerBI and Tableau • Handled Larger data sets Like 360 Peta byte and many Tera byte data using PySpark, Distributed training like ONXX,RAPIDS, Tensor RT,CUDA and Cloud GPU •Proficient in Model development, Model Training, Experiment, Re- Training, Active and Transfer Learning Validate, Testing, Prediction, Model Selection, Model Comparison- ROC-AUC, Evaluate Model Performance and Metrics, K-fold cross validation, Root Cause Analysis and Hyper parameter tuning • Implemented ML Ops practices like Data Version, Model Registry, Model Metrics, Data Drift, Model Drift, Ethics and Fairness, Explainable AI(SHAH and LIME) and Monitoring using AirFlow, MLFlow • Experienced with End to End ML infrastructure development and Multi Cloud model deployment for model training and prediction batch and real time • Communicate insights and recommendations to both technical and non-technical leaders and business customers/ partners. • Experienced using open source and commercial license OCR tools to scanned documents and perform downstream NLP analytics. • Performed A/B Tests on the client website and evaluated them to choose the winning member experience that provides Incremental Revenue and Sales • Experienced with Computer Vision using CNN,DALL-E-2,ViT,CLIP,VGG16, Resnet-50, Mask- RCNN and YOLO • Implemented RNN,LSTM,BERT,ChatGPT4,PALM-2,Deberta, Roberta,LLaMA-2,MPT and LangChain • Applied time series algorithms like ARIMA SARIMA, SARIMAX, Prophet, AR-DEEP (GluonTS) for forecasting • Experience with containerization and container-orchestration (ex Terraform, Docker and Kubernetes). • Experienced with Kafka, No SQL database like Cassandra,Neo4j MongoDB, Graph DB, Hive, Elastic Search and Milvus Vector DB