I am a Data Scientist with 7 years of experience and a PhD in Computer Science. My expertise lies in Generative AI/ML, data analyst and data engineer where I have gained valuable industry and academic experience. I am capable of developing innovative generative applications for clients and integrating on-demand Generative capabilities on existing systems. With a deep understanding of statistical methods and software tools, I can efficiently analyse large datasets.
Moreover, I possess expertise in data visualization, data cleaning, and data manipulation, which enables me to identify trends, patterns, and anomalies in data. I specialize in designing, building, and maintaining data pipelines that facilitate efficient data analysis. Additionally, I have knowledge in database design, data warehousing, and ETL (Extract, Transform, Load) processes.
With my skills and experience, I can provide valuable insights and help organizations make data-driven decisions. My commitment is to assist businesses in leveraging the power of Generative AI, transforming their ideas into valuable AI applications and models.
EXPERTISE AND EXPERIENCE:-
✅Skilled in using Generative AI techniques to identify production errors, anomalies, and defects from images. By leveraging deep learning models and computer vision techniques, I can provide rationale for issues and help improve the quality control process.
✅ Linear Regression and Logistic Regression: I possess expertise in statistical techniques such as Linear Regression and Logistic Regression, which are commonly used in machine learning for predicting continuous and binary output variables, respectively.
✅ Support Vector Machines (SVM): I am proficient in using SVM, a popular machine learning algorithm that is useful for classification and regression analysis by finding the hyperplane that best separates the data into different classes.
✅Big Data Engineering: Developing Data Lakes and managing Data Hubs, Web Scrapping, using Azure or AWS cloud services.
✅Experience with advanced forecasting and capturing demand in real-time from multiple data sources (structured data & unstructured data) and using integration hub data.
✅Time series analysis, financial forecasting, and other econometric methods.
✅Strong analytics background and hands-on experience in Financial modelling and analysis for budgeting and forecasting.
✅Experience in Data-driven decision making and trend analysis.
✅Robust Forecasting Model Library : Conjoint, KNN Analysis, Moving Avg, Regression, Exponential Smoothing, Holt Winter’s Model – Additive/Multiplicative, ETS-AAN, ARIMA, ARIMAX, SARIMAX, Neural network, Bootstrapping and ARCH/GARCH.
✅Technologies experience include:
§ AI Development Tools : Azure Open AI, Hugging Face, PyTorch, Streamlit, TensorFlow, GitHub Copilot, Keras, ONNX (Open Neural Network Exchange).
§ AI Models : Bard, BERT, ChatGPT, DALL-E, GPT-Neo, GPT-3, GPT-4, LLM, LLaMA, Open AI Codex, Midjourney AI, Stable Diffusion
§ AI Algorithms : Autoencoder, Generative Adversarial Network, Variational Autoencoder, Large Language Model, Transformer Model, Convolutional Neural Network,
StyleGAN, Transformer Model, YOLO
✅Artificial Intelligence / Machine Learning Models
§ Voice-enabled Chatbot that is available on the web and mobile and provides information using clinical, knowledge, and transactional database.
§ Chatbot and voice-enabled application transforming customer engagement.
§ Identification of suicidal markers from suicide notes for Dept of Forensic Medicine & Toxicology, AIIMS
§ Intraoperative surgical intelligence provides visual insights and information to surgeons in real-time.
§ Develop a platform that provides innovative insights to improve top line of pharma companies to a reality.
§ Hospital Cognitive Automation: State of the art AI Model to save millions of dollars for hospitals and reduce surgery rescheduling.
§ Created an ML agent to play the Hangman (a type of word game) game. In the hangman game player has to guess the letters of a secret word which is represented by a sequence of underscores.
§ Using real world data worked with Financial Time Series data. Used ARIMA type models to forecast Stock returns. Then using this model as input into the GARCH model to forecast volatility and ascertain Value at Risk.
§ World’s most complex intercompany accounting transaction system that is live at 37K locations.
§ Stock predictions and its analysis is rated #1 in the Fidelity Investments platform.
§ Data driven investment research and analytics to the financial community. Helping analysts leverage big data to improve model estimates and answer seemingly impossible questions
§ World’s #1 Account Management System (Used by IRS to Detect and Prevent Fraud)
§ Member Enrollment and Insurance Claim Processing Platform
§ Mud logging system provides real time mud