A highly motivated and intuitive individual, a team player with solid leadership skills able to generate new ideas, analyze, and resolve challenges. Creative, detail-oriented, flexible, and adaptable in changing environments.
I have experience in working with Data Science libraries in Python and R. My experience includes working with Data wrangling packages (dplyr/tidyverse), Visualization packages (ggplot), Modelling, Time Series Analysis, Machine Learning Algorithms and Big Data operations for Spark. I also have experience working in Tree-based models in Supervised Learning (Gradient Boosting, Random Forests, and Decision Trees) and Clustering in Unsupervised Learning (K-means and Hierarchical Clustering). Also, proficient in MySQL and PostgreSQL
I have great enthusiasm for working with real-world data sets to optimize business processes and find underlying patterns.
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Experience
• Worked with users to obtain user input on recommended Data Quality checks leveraging UI.
• Demonstrated Foundational UI Framework for Data Quality Measurement showcasing recommended Data Quality checks.
• Developed ML models and used UI to display completeness exceptions that do not meet the desired threshold.
• Created ML Assisted Anomaly Detection Solution to detect Data inconsistency anomalies based on Python-based ML Models.
• Presented Data Quality Dashboards to capture Data Quality Exceptions in a Custom Data Model thus enabling users to understand data inconsistency issues.
•Gathered requirements from end-users and worked with Subject Matter Experts (SME), the project team (business and technical), to define business and system requirements.
•Performed Product testing and identified bugs within the application. Interacted with the development team in fixing defects to resolve issues before deadlines.
•Wrote SQL queries for data analysis and data extraction from large data sets.
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Projects
• Viacom (Experiential Learning)
Determined the importance of digital marketing on the demographic-based products and used the ML algorithm to formulate a strategy in devising a cost-effective solution for driving the maximum number of Call to Actions on the Viacom page.
• Movie Recommendation System
Used Big Data technologies to analyze large volumes of datasets and build a movie recommendation model by studying historical data.
• Data Visualization using Tableau
Prepared dashboard for data visualization using Tableau and R for Healthcare Claims dataset demonstrating hidden relationships, key patterns, anomalies, and trends in the data.
• Statistical Analysis of Healthcare Data
Constructed the Logistic Regression model (Predictive Analysis) using R to detect future heart conditions.
• Behavioral Analysis of Customers
Used Data Mining concepts for Predictive analysis for the future impact of customers on Black Friday sales.