Hi there, I'm Mahendra 👋
DataScientist with AI Expert
& ML/DL/NLP Generative AI Engineer
The journey from raw data to impactful solutions is what truly excites me.
A highly dedicated and results-oriented Data Scientist with a passion for
solving complex business problems with enthusiasm
.png)
There's no greater satisfaction than building end-to-end pipelines, deploying models strategically, and developing ML DL NLP Generative AI products that solve complex business problems.
Gained hands-on experience in cutting-edge Generative AI techniques and cloud technologies while working as a Data Scientist at Geak Minds. Applied advanced methodologies, including Retrieval-Augmented Generation (RAG), AI Agents, SQL Agents, and LLM Summarizers, to create innovative solutions such as Chatbots for Q&A systems and fine-tuning Large Language Models (LLMs) for domain-specific tasks.
Leveraged tools like Microsoft Fabric and Azure Data Fundamentals to architect scalable and efficient data solutions. Built expertise in working with Transformer-based architectures, contributing to the development of next-generation AI applications.
Skills: Generative AI- RAG, AI Agents & SQL Agents, LLM Summarizer, Chatbot-Q&A, Finetune LLM , Microsoft Fabric, Azure Data Fundamental, Transformer
At CodeClause, I developed a sentiment analysis pipeline using data preprocessing, pre-trained GloVe embeddings, and a model with Convolutional and LSTM layers, integrated into a Flask web application with a user-friendly HTML and Bootstrap frontend.
I also implemented MongoDB to store user reviews, providing real-time sentiment feedback for a seamless and robust user experience.
Skills: Python oops, Datascience lifecycle stages, Training pipeline, Prediction pipeline, GitHub, Github actions, Html, Flask, Machine Learning, Docker, MLOps, Docker hub, DVC, Azure
Developed an end-to-end customer attrition prediction application at Codesoft, including setting up a virtual environment and a collaborative GitHub repository.
Built a robust training pipeline with ordinal encoding, ADASYN, and SMOTE techniques, achieving 99.17% accuracy using the Extra Tree Classifier. Developed a user-friendly interface with Flask and HTML, and deployed the application on an Azure cloud server using Docker and DVC for version control and resource optimization.
Skills: Got awareness of solving problem statements , Preprocessing techniques, Model Building, Model Evaluation, Deployment, DVC, Docker, Building pipelines from data ingestion to mode evaluation
Gained hands-on experience in the latest data science and machine learning techniques, working under experienced mentors. Applied Python programming and utilized libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, TensorFlow, and PyTorch for projects including deep learning algorithms, computer vision, and NLP.
Thrilled to contribute to a data science organization, passionate about expanding knowledge and bringing creative strategies to future roles in the field.
Skills: Python libraries and frameworks, NLP, Deeplearning, Datascience lifecycle stages, Training pipeline, Prediction pipeline, Git & GitHub
I led a team of 7, developing a PyPI-published automated MongoDB Database connector in Python venv 3.8. I managed dependencies, conducted rigorous testing, automated setup with init_setup.sh, and implemented CI/CD for smooth deployment, significantly enhancing MongoDB connectivity and developer productivity.
Skills: Unit Testing, Integrate testing, MongoDB, Python package Development, Pipy, CI-CD
LOVELY
PROFESSIONAL
UNIVERSITY
Bachelor of Technology
April 2020 - May 2024
Computer Science Engineering,
Specialization in Data Science
