Shivakumar Km
Bangalore,Karnataka
Summary
Data Science Professional Experience: Over 10v years in the finance, retail, and healthcare domains. Machine Learning: Proven track record in developing machine learning algorithms to solve complex business problems. AI Application Architecture: Skilled in designing AI application architectures, ensuring scalable and efficient solutions. Code Review Expertise in conducting code reviews to maintain best practices in style, accuracy, testability, and efficiency. Documentation & Educational Content: Significant contributions to creating and updating documentation and educational content, adapting materials based on product updates and user feedback. Problem Solving: Proficient in triaging and resolving product/system issues, performing root cause analysis, and assessing impacts on operations and quality. Computer Vision: Experienced in developing computer vision-based customized object detection systems for low-resource hardware and Android platforms. Research & Development: Capable of reviewing research papers in vision, NLP, and speech, as well as drafting and implementing new procedures and work instructions.
Overview
20
20
years of professional experience
Work History
Senior Manager, Data Sciences
Axiscades Technologies Ltd
07.2023 - Current
- AutoCon - Concession Management System
- Client: Airbus
- Developed and deployed a VectorDB to store and transform concession documents for different aircraft types, improving data storage and retrieval efficiency
- Applied sentence transformer embeddings for document clustering, enhancing document organization
- Implemented a query system on the VectorDB to retrieve semantically similar documents, improving information retrieval
- Developed an in-house PDFMatcher module to recommend concession documents, reducing turnaround time for resolving aircraft defects
- Used: Python, ChromaDB, Langchain, Sentence, , Scikit-learn, Kafka, Docker
- NC-Answering Data Retrieval Tool
- Client: Airbus
- Developed an OCR engine to extract tables and blocks of interest from non-editable PDF documents, automating data extraction
- Created an in-house module to process OCR outputs, enhancing data accuracy by aligning extracted data
- Tools Used: Python, PyTorch, DocTR, DB-ResNet, CRNN-VGG16, esnet50, Scikit-learn, Kafka, Docker
- NC Answering QnA App
- Client: Airbus
- Developed a RAG-based non-conformity answering tool using GPT-3 and Langchain, improving response accuracy to non-conformity queries
- Integrated semantic search and document embedding capabilities for contextually relevant answers
- Deployed on AWS, ensuring scalability and robust performance
- Tools Used: Python, Langchain, GPT-3.5, Sentence Transformer, ChromaDB, FastAPI, Docker, AWS EC2.
Lead Data Scientist
UST Global
01.2018 - 09.2020
- Risky Contract Document Categorization
- Developed models to classify documents into risky and non-risky categories, enhancing risk management
- Tools Used: Python, NumPy, Pandas, NLTK, Scikit-learn, BeautifulSoup, Adobe Reader, Jupyter Notebook, AzureML Toolkit
- Smart-Sense
- Developed speech-to-text conversion models for varied accents, improving customer interactions
- Applied sentiment analysis and text analytics to classify customer interactions and identify trends
- Tools Used: Python, NumPy, Pandas, Scikit-learn, SciPy, PyAudio, TensorFlow, Keras
- Anomaly Detection in Server Logs
- Developed models for detecting anomalies in server usage, helping prevent downtime
- Tools Used: Python, NumPy, Pandas, Scikit-learn, SciPy, Numenta, Statsmodels.
Corporate Trainer
07.2017 - 12.2017
- Delivered training on data science and machine learning principles.
Lead Data Scientist
Baatu Mobile
08.2004 - 07.2017
- Key-Phrase Extraction
- Developed a model to filter key phrases from various sources, enhancing content identification
- Trained a Naive Bayes classifier to categorize children's hobbies, contributing to behavioral analytics
- Tools Used: Python, NumPy, Pandas, Scikit-learn, Flask, AWS EC2, S3
- Object Detection
- Developed computer vision-based object detection models for Android, improving machine learning applications in mobile environments
- Scaled down model size for deployment on hardware devices with limited resources
- Tools Used: Python, PyTorch, YOLOv5, ONNX, NCNN, Vulkan, AWS EC2, S3, FastAPI., Focused on teaching and research in NLP and data science
- PhD in NLP
- Research Publications available on Academia.edu.
Applied NLP Research
01.2013 - 01.2017
- Gained expertise in machine learning, computational intelligence, speech and language processing, and optimization theory.
Education
M.Phil - Computer Science
MK University
2008
MCA (Master of Computer Applications) -
VTU
2003
Skills
- Technical Skills
- Programming Languages:
- Python, PySpark, Java, C, C, Chaquopy
- Machine Learning Frameworks: TensorFlow (CNN, RNN, transformers, YOLO, Time Series Prediction), Scikit-learn, PyTorch, Langchain, LangSmith, LangServe, LangGraph
- ML Model Management: MLFlow, AWS SageMaker
- OCR Engines: DocTR, PyMuPdf
- Generative AI Tools: GPT-3, GPT-4, Sentence Transformers, LlamaIndex, llama-cpp-python, prompt engineering, custom LLMs, LMMs, RAG-LLMWare
- NLP Tools: NLTK, Spacy, CoreNLP, Hugging Face Transformers, BERT-NER
- Databases: ChromaDB, PostgreSQL, MongoDB
- Development Tools: Git, Docker, AWS
- REST API: Flask, FastAPI, Streamlit
- Cloud Deployment: AWS (EC2, S3, RDS, SageMaker)
- Hardware Integration Libraries: NCNN, Vulkan, ONNX, OpenVINO
- Optimization: Functional and resource optimization in data science development
Timeline
Senior Manager, Data Sciences
Axiscades Technologies Ltd
07.2023 - Current
Lead Data Scientist
UST Global
01.2018 - 09.2020
Corporate Trainer
07.2017 - 12.2017
Applied NLP Research
01.2013 - 01.2017
Lead Data Scientist
Baatu Mobile
08.2004 - 07.2017
M.Phil - Computer Science
MK University
MCA (Master of Computer Applications) -
VTU
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