Result oriented professional with experience in Data Analysis, Predictive modeling and reporting. Proficient in attention to detail, project management and working with several teams.
• Languages and Services: R, Python, AWS ML services
• Databases: Snowflake, PostgreSQL, MySQL, Amazon Redshift
• Data Visualization: MicroStrategy, Tableau
• Certifications: AWS Cloud Practitioner, Google Advanced Analytics
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Experience
Analyst, Customer Analytics – Vibes, Chicago
Nov’18 – Present
Progressed from an intern position to full time Analyst. Responsibilities include understanding customer’s business and leverage data to build and optimize digital marketing solutions.
• Automated 15+ business critical reports, saving 10-15-man hours per week and reducing manual error to zero
• Analyzed customer data to help stakeholders build marketing strategies, resulting in lift of 2% in MoM acquisitions
• Built advanced analytics frameworks to improve marketing performance using ensemble models consisting and not
limited to PCA, clustering, RandomForrest classifier and XGboost
• Used NLP techniques to segment customer messages based on their sentiment and recommended campaign strategies,
resulting in 6-8% increase in conversion
• Performed A/B testing on models designed for growth and creating value for upsell
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Projects
Next Purchase Day Prediction
• Analyzed the e-commerce purchase behavior of shoppers to predict the days-range for next purchase
• Created RFM clusters, cross-validated different models and tested with real world data to get an accuracy of 60%
Data Analysis of Airbnb prices in Chicago
• Provided statistical analysis of factors that affect prices of Airbnb listings in the city of Chicago
• Applied data cleaning, hypothesis testing and regression techniques in R to achieve an accuracy of 46.7%
WhatsApp Based Recommendation System
• Leveraged the AWS Personalize to recommend consumer products based on user preference over WhatsApp • Scrapped data from e-commerce retail website, used API calls to trigger AWS personalize results
Market Basket Analysis
• Performed analyses on online retail data of 540K transactions to get frequently bought items