SUMMARY
I am a Data Scientist, currently working at Volkswagen (Scania), contributing to real-world AI projects with hands-on experience in deploying and fine-tuning both classical and transformer-based models such as BERT, GPT variants, and publicly available LLMs. Skilled in leveraging cloud platforms like AWS, including AWS Bedrock, for scalable AI/ML development. Experienced in implementing MLOps/LLMOps practices for model lifecycle management, automation, and observability. Proficient in orchestrating AI workflows using Kubernetes and building robust NLP and Generative AI solutions.
WORK EXPERIENCE
- Data Scientist | AI/ML Consultant – Volkswagen Group Technology Solutions India, Gurugram (Nov 2024 – Present)
- End-to-end involvement in AI/ML project lifecycles from problem scoping to deployment and monitoring.
- Principal Consultant – NSE TalentSprint, Hyderabad (April 2021 – Oct 2024)
- Led and coordinated academic and operational teams.
- Designed industry-relevant projects and assignments in ML and Generative AI.
- Delivered lecture sessions on advanced AI topics.
- Research Fellow – IIT Delhi (March – May 2019)
- Project: Energy Efficiency and Occupant Comfort Management in the Built Environment.
- Responsibilities: BMS data collection, analysis, and modeling.
- Assistant Professor – Thapathali Campus, Kathmandu, Nepal (June 2015 – Dec 2016)
- Lecturer – Sagarmatha Engineering College, Kathmandu, Nepal (Nov 2011 – May 2015)
ACADEMIC DETAILS
- M.S. Mechanical Engineering (Thermal Science), IIT Delhi, 2019
- B.E. Mechanical Engineering, T.U. Kathmandu, Nepal, 2010
TECHNICAL SKILLS
Machine Learning, MLOps, Deep Learning, Computer Vision, NLP (BERT, GPT, ChatGPT, T5, LLMs) | Python (NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow/Keras, PyTorch) | AWS (SageMaker, Bedrock, S3, EC2, ECR, ECS, Fargate)
COURSES (Relevant to DS/ML)
- Computer Programming
- Probability and Statistics
- Linear Algebra
- Numerical Methods
- Differential and Integral Calculus
- Engineering Economics
- Experimental Methods
- Economics & Planning of Energy Systems
- CNN, Neural Networks & Deep Learning, Sequence Models
IIT DELHI THESIS
- Title: Performance Analysis of an In-situ Data Center
- Supervisor: Prof. Sanjeev Jain
- Energy analysis using data analytics, multivariable regression, and neural networks.
- Airflow and thermal distribution analysis using Ansys ICEPAK (CFD).
- Outcome: Identification of energy conservation opportunities.
SCHOLASTIC ACHIEVEMENTS
- Merit-based full scholarship admission to Pulchowk Campus, Nepal.
- Best Project Award – HVAC domain, IIT Delhi (2018–19).
PERSONAL PROJECTS
- Classical Machine Learning Implementations
- Credit Card Fraud Detection
- Loan Amount Prediction
- Housing Price Prediction
- CNN Transfer Learning – HF Spaces
- Image Segmentation (UNet, DeepLabV3+)
- RAG-based LLM Applications
- ML in Production – CI/CD & Packaging