FulfillmentEnrollmentRx ClaimsAzure, ADF, Blob Storagedata developmentETLManaging Database flow Root cause analysiscontinuous program developmentHealth care Satisfaction Survey data

• Developed a dashboard for analyzing Masters Student Satisfaction Survey results at Franklin University using Python, SAS, and Microsoft Excel under the guidance of Dr. Yuerong Sweetland.• Worked on the Course Tally project, which involved categorizing college data using Python and Excel macros.• Responsible for data identification, collection, exploration, cleaning, and modeling.• Used Pandas, NumPy, seaborn, SciPy, matplotlib, and Scikit-learn to visualize the data after removing missing and outliers to fit in the model.• Performed and treated outliers and missing values detected using boxplots and Pandas predefined functions.• Worked with dimensionality reduction techniques like PCA, LDA, and ICA.• Also used t-SNE (t-Distributed Stochastic Neighbor Embedding), UMAP (Uniform Manifold Approximation and Projection).• Worked with the Regression model, which includes Random Forest regression. Lasso Regression.• Worked with various classification algorithms, including Naïve Bayes, Random Forest, Support Vector Machines, Logistic Regression, etc.• Also worked with K-Nearest Neighbors Apriori algorithms for product recommendations, including content-based and collaborative filtering methods.• Applied Clustering algorithms such as K-means to categorize Student's data into certain groups

Client: Takeda Pharmaceuticals• Using Python and Machine Learning concepts, we streamlined ServiceNow tickets and created an automated ticket classification system.• Implemented an internal Dashboard tool to integrate all business units into a centralized dashboard, facilitating project status reviews and enhancing collaboration across teams.• Engaged in client collaboration to gather and comprehend business requirements, effectively translating them into data-driven solutions.• Collaborated with cross-functional teams, including developers, data scientists, and project managers, to ensure seamless integration and successful implementation of solutions.• Finding patterns in complex data sets, Data Analysis and Interpretation, Database and Reporting Knowledge

Client: Disney, GM, Purina, Unilever, GoogleData: e-commerce data, entertainment, health care, supply chain• Lead designing and developing a comprehensive Disney project dashboard, integrating KPIs, drivers, and barriers for streamlined visualization and decision-making.• Created SPSS macros to handle ad-hoc research efficiently, removing 60% of manual work, enhancing data analysis, and boosting operational effectiveness with creative ideas.• Identify and measure the success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.• Data sourcing from many platforms to convey the tale of what happened and provide suggestions on how to continuously enhance the business's performance in satisfying consumer expectations. • Ensured high accuracy and quality of data files for optimal analysis, brand strategy, and product development by spearheading data gathering business requirements, data manipulation, data cleaning, and preparation.• Effortlessly worked alongside researchers to extract valuable insights from market research surveys and enhance research outcomes while seamlessly integrating model performance management tools into the existing business processes infrastructure.• Demonstrated proficiency in SPSS and Quantum scripts, skillfully executing data merging, stacking, weighting, and tabulation, hypothesis testing to enhance data quality and usability.• Engaged with customer needs to tailor survey questionnaires, leveraged Excel, SPSS, and SQL for precise data analysis, and conducted comprehensive statistical techniques to uncover significant insights.• Extracted data and worked with data from different databases for oracle, SQL server, DB2, NoSQL, PostgreSQL, MySQL and analyzed data using analytics tools such as Python, R, and/or SAS, SPSS.• Creating business values by utilizing data trends, industry insights for campaigns, and smart executive insights on consumer patterns.

Data Processing Project Involvement:• Led data cleaning and preparation efforts, ensuring accuracy and quality of data files.• Generated tables and visualizations for client presentations, enhancing data-driven decision-making. Collaborative Research and Insights:• Collaborated closely with researchers to extract valuable insights from questionnaires.• Contributed to the interpretation and analysis of questionnaire data, aiding in research outcomes.Technical Proficiency:• Proficient in utilizing SPSS and Quantum scripts for data cleaning and preparation.• Executed data stacking, weighting, and tabulation, optimizing data quality and usability.

Adhoc porjects, Market research data processing analyst• Collaborated closely with clients to develop survey questionnaires and guidelines, tailoring them to capture relevant information and meet research objectives.• Utilized Excel, SPSS, and SQL to conduct surveys and analyze data, ensuring accurate and reliable results.• Conducted statistical analysis of large data sets using tools such as SPSS, SAS, and Excel, applying appropriate statistical tests and techniques to extract meaningful insights.• Ensured data integrity by implementing rigorous data cleaning techniques, identifying, and resolving data inconsistencies and errors.• Demonstrated strong attention to detail in all aspects of survey research, including questionnaire design, data analysis, and report generation.