Next-Gen AI for Capital Markets - Fundamentals, Bonds and ESGManaging a team that includes data scientists and data engineersSome of the problems we are working on : Computer Vision : 1. Extracting Characters/data from noisy images 2. Detection and Extraction of data from PPTs, PDFs 3. Document Layout detection 4. Image enhancement 5. Extracting data from charts 6. Signature detection and verification LLM: 1. Custom LLM for Financial Data 2. Document QA NLP : 1. Converting unstructured data to a structured format 2. Document/Page/Sentence Classification engine for ESG, Financial, and Covenant documents 3. Multi-document Summarization 4. Abstractive Summarization 5. Relation Extraction 6. Question Answering Systems 7. Language Translation Multimodal Learning: 1. Visual QA Systems Video : 1. Liveliness Detection Tech Stack : Python, Docker, Kubernetes ML Stack : Pytorch, Sckit Learn Note : We have openings at all levels.

Worked on various NLP problems : Sentiment analysis (Document Level and Entity Level ), Named Entity Recognition (Both Editorial and Social), Named Entity Disambiguation , Finding Similar Documents , Document Categorization, Text Summarization, Intent Detection, Noun Chunker detection, Relation Extraction/Classification Working on Deep Learning and Machine LearningBuilt models for languages : English, Spanish, German, Norwegian, Hindi, PortugueseDeep learning Packages : Tensorflow, KerasMachine learning Packages : Scikit learnOthers : git, docker, aws, terraform ,kubernetes

Work includes:- Extracting sentiments/opinion from text using Natural Language Processing Techniques.- Forecasting Stocks using various machine learning algorithm.- Topic Modeling

Worked on :1. Opinion Mining2. Social Network Analysis3. Extracting Key Topics from text4. Forecasting algorithms

Worked on Market Mix Modelling,Statistical Analysis,Opinion mining,Forecasting.Yield,Clustering and Segmentation.

Worked as Assistant System Engineer