- Accumulated 17+ years of data science and engineering experience in the Banking, Monitoring, Media and Entertainment domains, working with clients worldwide, including Australia, USA, China, and India. - Recognized for authoring and filing 3 patents encompassing Gen AI LLM model optimization, NLP/Stream analytics, and Data sampling for training ML algorithms. - Secured victory in a global organizational Hackathon and contributed multiple innovative ideas in the realm of AI/ML. - Proficient in Gen AI use cases, adept at applying and fine-tuning LLM models to implement generative AI in existing products for multiple textual use cases, utilizing Langchain and Lora adapters. - Skilled in kdb+ and q programming languages, leveraging their robust data storage, retrieval, and manipulation capabilities. - Applied advanced time-series analysis techniques, such as forecasting, trend analysis, to derive valuable insights. - Pioneered the implementation of end-to-end AI/ML solutions for Business service failure prediction through state-of-the-art online/incremental learning on streaming data. - Spearheaded the development of an end-to-end anomaly detection solution for Log Analytics prediction using real-time anomaly detection employing NLP and Autoencoders. - Designed and engineered an in-house DataOps pipeline in Python/pyspark, streamlining the data engineering process and automating complex data dependencies. - Architected a federated learning solution to train machine models remotely and ensure secure data transfer. - Integrated a CICD pipeline to automate git, unit test, and code scan processes, streamlining development workflows. Tools and technology: • AI areas: Predictive analytics, Timeseries, Deep-NLP (text data), Stream data, Big data, Recommendations, Federated learning. • AI Algorithms: ANN, RNN, LSTM, Autoencoders,BERT, XGBoost, Logistic Regression, Linear Regressopm,SVM, K- means clustering, Decision Trees,KNN,Linear regression, Principal Component Analysis, Multi arm bandit (Reinforcement learning), Statistics •GenAI models:Mistral, falcon, llama2, gpt series, alpaca and more • AI Language and tools: Python, Spark, Keras, Tensor Flow, Scikit Learn, Numpy, Pandas, spacy, word2vec, gensim, glove • Timeseries DB - kdb+ • Micro services for AI : Flask • .NET: C# • UI : Angular, D3.js • Security and Performance: AppDynamics, fiddler