Hello! I'm Sancharika Debnath, a passionate Data Scientist with a knack for leveraging emerging technologies to create innovative solutions. My expertise spans data science, machine learning, back-end development, and generative AI, and I'm always eager to explore new challenges and opportunities.

• Developed an agile event system integrating facial recognition, object identification, and GPS with 87.4% accuracy.
• Collaborated on Neo4j architecture for data mining, using REST API and GCP.
• Delivered a custom public API for 1.3M+ Indian education institutes via Elasticsearch and web scraping.
• Designed a Generative AI stack Bot boosting interaction by 90% using Dialogflow, Firebase, OpenAI, and GPT.

• Created a customized back-end and Django REST API for a website with 50+ advisors, focusing on feature optimization using CI/CD tools.

• Developed an office seat pre-booking web app, boosting booking efficiency by 80%.
• Enhanced analytical capabilities with clustering models and Gaussian Mixture for cost estimation.
• Predicted container turn time and forecasted attachment-ratio using FLAML and Azure ML.

• Created a regression invoice prediction system with XGBoost, achieving 76.15% accuracy.

• Programming Languages: Python, C++, R, Java, JavaScript
• Technical Skills: NLP, Machine Learning, Deep Learning, Computer Vision, Data Analysis, Generative AI
• Libraries: Pandas, NumPy, SkImage, TensorFlow, PyTorch, scikit-learn, Keras, OpenCV, NLTK, spaCy, Transformers
• Tools: AWS, Azure, GCP, Neo4j, Cassandra, Pinecone, SQL, Tableau
• Frameworks: Keras, TensorFlow, PyTorch, LangChain, Llama, Django, PySpark, GitHub, Databricks, Azure ML

• Career Enchanter: Developed a Generative AI data pipeline for job hunting, including resume reviews, personalized recommendations, cover letter generation, and ATS score calculation using BERT Transformer and Large Language Models.
• LLM IPO Analyzer: Built a Generative AI/ML model for detailed investment statistical analysis in startup IPOs using Llama, HuggingFace, and LangChain.
• Furniture Classification: Developed a furniture classifier using deep learning models and Transfer Learning, achieving 83.16% accuracy with ResNet-50 on AWS SageMaker.

• Hyperspectral Image Compression: Conducted research on HSI using CNN bottleneck AutoEncoder, achieving 0.998 accuracy, published in IJCISIM.

Kalinga Institute Of Industrial Technology, Bhubaneswar, Orissa, India
Bachelor of Technology, Information Technology
CGPA: 8.83
(June 2019 - July 2023)

Feel free to reach out to me via LinkedIn, X or Email. You can also explore my projects and contributions on GitHub.

Thank you for visiting my profile! Let's build something amazing together. 🚀👩‍🎓