Data Science

Data Science

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  • Delivery Time 1 Month
  • Response Time 3 Hours
  • English Level Professional


  • 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

About The Seller

A singh

Data Scientist

  • Location:

Starting From
Service charges $0.00

Ref #: 6406

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