Varsha Rathore

• Conducted exploratory data analysis (EDA) to identify key business insights, improving decision-making processes.
• Collaborated with cross-functional teams to define and track key performance indicators (KPIs).
• Utilized SQL and Python for data extraction, transformation, and loading (ETL) processes.
• Created interactive dashboards using Tableau to visualize data trends and insights.
• Assisted in the development of algorithms and predictive models to extract and analyze large volumes of data.
• Collaborated in cross-functional teams to implement data-driven strategies.
• Contributed to achieving business goals by providing data-driven insights and helps to take decision.
• Worked on KNIME for marketing analytics.

1. Ed Tech company analysis: The EdTech Lead Generation project aims to explore the dynamics of lead acquisition
and conversion within the rapidly growing online education industry. With the surge in demand for online
education due to factors like convenience, personalized learning experiences, and the recent impact of the Covid19 pandemic, the project seeks to understand how EdTech companies attract and nurture leads to convert them
into paying customers.
Skills and Tools: Logistic regression , Decision Tree
model and Linear Discriminant analysis

2. The Pricing Optimization project for Hotel stays aims to develop a strategic pricing model for properties listed on the
Airbnb platform to maximize bookings and revenue while remaining competitive in the market. With close to 150
million customers worldwide, pricing plays a crucial role in attracting and retaining customers. By understanding
the factors that influence pricing decisions and leveraging data-driven insights, the project seeks to optimize
property prices to meet customer expectations and stay ahead of competitors.
Skill and Tools : EDA, univariate ,bivariate analysis and
Linear Regression.


3. The XYZ Bank Credit Card Customer Focus project aims to enhance customer penetration and satisfaction
within the credit card customer base through targeted marketing campaigns and improved service delivery. With
the goal of improving market penetration and addressing customer perception of support services, the Marketing
and Operations teams have identified the need for personalized campaigns to attract new customers and upsell to
existing ones, as well as a service delivery model upgrade to address customer queries more efficiently.
Skills and Tools: EDA,Clustering


4. The Visa Approval Prediction project aims to develop a machine learning-based solution to facilitate the
process of visa approvals for temporary and permanent labor certifications processed by the Office of Foreign
Labor Certification (OFLC). With the increasing number of applicants each year, there is a need for an automated
solution to help shortlist candidates with higher chances of visa approval, thus reducing the tedious task of
reviewing every case manually.
Skills and Tools : EDA,Bagging classifier, Random
Forest and Ada- boost classifier.

5. Worked on Maketing Analytics technique like RFM and market basket analysis.

6. Car claim insurance analysis using Tableau to fetch more insights from the Data.