Business Analytics graduate with a little over a year of experience in Analytics. Skilled in Data Analysis and Data Visualization. Analytical and Practical problem solver, work well under pressure, and adaptable to changing business needs. Possess strong interpersonal, time management, and organizational skills. I am in the process of looking for my next opportunity in Business and Data Analytics.
• BI/Reporting Tools: MS Excel (Advanced), Tableau, Power BI, SAP Business Objects & SAP HANA, QlikView
• Databases: SQL, MongoDB -Studio 3T
• Programming: R, Python, SAS, STATA
• Machine Learning & Data Science: Regression Techniques, SVM, PCA, KNN, Decision Trees and Random Forests, K-Means Clustering, Time Series Analysis, Natural Language Processing, Neural Networks
• Certifications & Courses: AWS for Data Analytics, Google Analytics Individual Certificate, Pricing Analytics
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Experience
• Worked on Quantitative Analytics and Strategy planning for 3+ pharmaceutical consulting projects
• Supported testing and maintenance of Asset-based Valuation Model for pharmaceutical intangible assets, R&D expenditure, and cash flows
• Quarterly and Yearly Forecasting using Sales and Revenue data using Demand and Trend Projection methodologies
• Provided reporting for 5-year forecast analysis and ad hoc reporting to support decision-making.
• Conducted deep-dive data analysis and provided executive-level reporting on the client's current business and future opportunities
• Applied knowledge of financial data modeling and statistical analysis to note trends and draw conclusions.
• Support maintenance of forecast accuracy by using historical trends, secondary data and input from SME to create a quality forecast for a designated area of responsibility
• Awarded “SPOT” award for performance in the consulting project associated with "Valuation Model" Forecasting Project
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Projects
CPAL Opportunity Index| Python, Tableau
• Consulting Data Analytics Practicum sponsored by Child Poverty Action Lab, an initiative of City of Dallas to identify Opportunity Zones in and around Dallas
• Used Exploratory Data analyses, Classification and Regression models in Python to distinguish between high opportunity and low opportunity areas and implemented appropriate strategies with Tableau reporting to increase affordable housing access for lower-income families in such zones
Prediction of Chance of Admit| SAS, R
• Developed a model to estimate chances of getting university admits by selecting the most accurate model to predict the probability of admission
• Implemented Factor analysis to describe variability among observed, correlated variables and Regression analysis (Linear, Logistic and Probit) to develop the model
Integrated Analysis - Decision Tree and K-means Clustering| R, Tableau
• Used Decision Tree to predict key variables in classifying ratio of survived: Not survived in Titanic data and K-means Clustering for Classification
• Calculated Optimum number of clusters was visualized in Tableau using the integrated analysis to examine clusters and attributes in clusters that have the highest survivability
Capstone-Yelp Reviews|Python
• Used Naive Bayes Classification to classify reviews on yelp into 1-5-star categories based off text content in reviews