Rushabh Bhagwati Parikh

A highly skilled Data Scientist with 1.7 years of experience in Data Analytics, Machine Learning, and Deep Learning techniques, along with over 7 years of expertise in Mathematics and Statistics. With a strong academic background, I excel at conducting statistical data analysis, building predictive models, and performing time series analysis. I have extensive experience working with Machine Learning and Deep Learning algorithms, as well as Large Language Models (LLMs) and LangChain for Generative AI applications. Proficient in using Azure Data Factory for ETL processes and skilled in data visualization with Power BI, I am committed to delivering data-driven insights that drive business growth and support decision-making.

Text to SQL Query Generation and converting to Natural Language for End User 

• Developed an AI chatbot capable of providing answers from a large SQL database.

• Utilized the LangChain framework to create the chatbot and employed the Mixtral Instruct 7B model as the LLM for SQL query generation. 

• Leveraged technologies including Python and SQL. 

• Utilized libraries such as Torch, Transformers, LangChain Community, SQLAlchemy, and Hugging Face to enhance functionality and performance.

ETL and Data Analytics for Nexum

• Analyzed the company’s invoice history and analytics for Nexum. 

• Designed and implemented ETL workflows using Azure Data Factory to extract data from the source SQL database. 

• Created data flows in Microsoft Fabric to establish a dummy database. Developed Power BI reports based on financial KPIs. 

• Built a time series model for predicting the company’s current balance. 

• Technologies Used: Python, Azure Data Factory, Microsoft Fabric, Power BI, SSMS

Forecasting of Nifty50 Index  

• Predicted the Indian Nifty50 index for the year 2022-2023 using R programming.
• Technologies Used: R Programming.

Predictions of Insurance Fraud of the Customers  

• Conducted exploratory data analysis and predictions to identify whether customers are fraudulent using various machine learning models in R programming.
• Employed models including Logistic Regression, XGBoost Classifier, Random Forest Classifier, and Decision Tree Regressor.
• Technologies Used: R Programming.

Drug Name Detection 

• Developed a customized Named Entity Recognition (NER) model using Deep Learning technique LSTM to identify drug names from text data with 90% accuracy.
• Utilized libraries named Pytorch, Spacy, Numpy, Transformers, Scikit-learn etc.
• Technologies Used: Python.

• Selected for MTTS (Mathematics Talent and Training Search) at IIT Madras, attended a one-month workshop in Mathematics.
• Selected for TPM, 2017 at NISER, Bhubaneswar, and participated in a one-month Mathematics workshop.
• Attended a 13-day Mathematics workshop at IIT Patna at the India Level.
• Passed Prof A. R. Rao Mathematics Competition.
• Passed Minaxi Lalit Mathematics Competition conducted by USSC, Gujarat University, Ahmedabad, Gujarat.
• Passed Gujarat State Eligibility Test (GSET) in 2020.

• Date of Birth: 01/24/95
• Nationality: Indian
• Marital Status: Unmarried
• Religion: Hindu