Description
- As a Freelancer Data Scientist, I have worked on following:
- Analytics & Machine Learning Methodologies
- Conducted extensive research on revenue management and pricing analytics in the hospitality sector
- Applied various machine learning techniques to build dynamic pricing models and maximize profits
- Gathered pricing data from different aggregators by performing web scraping in Python for competitive analysis
- Optimization & Algorithm Development
- Developed an algorithm for yield management using the concept of price elasticity of demand
- Deployed multiple loss minimization & optimization techniques
- Statistical Modelling & Analysis
- Created multivariate regression-based attribution models using ad stock analysis from digital marketing data
- Developed segmentation models using K-means Clustering for exploring new user segments
- Conceptualized and implemented a sentiment analysis tool to rate hotels based on subjective customer reviews
- Project Summary:
- Domain: Consumer Relationship Management | Tech Stack: Python |
- Objective: Consumers more likely to dispute a conclusion can be given more attention while conveying the final conclusions
- Solution: Designed a machine learning model via logistic regression to predict consumer complaints
- Key Achievement: Developed a model with an AUC score of 0.50
- Domain: banking | Tech Stack: Python |
- Objective: Understand how the bank approves and refuses loan. Find out different patterns and represent the outcomes to help the bank reduce the credit risk and interest risk.Solution: Used EDA With plots to to understand how consumer attributes and loan attributes influence the tendency of default.
- Key Achievement: Predicted which consumer can pay the loan.
- Domain: Ed-Tech | Tech Stack: Python, Pyspark, AWS |
- Objective: In this the client asked to develop a model in which students opting for course are about 80%.
- Solution: Used Apache Spark , ApacheHadoop Map Reduce to develop my model.
- Key Achievement: Developed a model in which i clearly converted leads to almost 80%.
- Domain: E-Commerce | Tech Stack: Python, Pyspark, Azure ,SQL |
- Objective: In this the client asked to develop Analytics data warehouse for an e-commerce company.
- Solution: Used Apache Spark , ApacheHadoop Map Reduce ,sql, database development to develop data warehouse
- Key Achievement: Developed a complete data warehouse
