Jawwad Kiani

Designed and built data analytic solutions from concept to implementation in an agile environment. Created pipelines in Azure using Azure Database Factory to get the data from disparate source systems by using different activities like Move & Transform, Copy, filter, for each, Databricks etc.

Performed data analysis to understand the main drivers of membership businesses and price elasticity of the brand. Developed statistical models for regressions, classifications, clustering, and time series analysis using Jupyter notebook.

Performed data cleaning processes, applying backward and forward filling methods for handling missing values, and performed one-hot encoding, feature scaling, and normalization using Jupyter Notebook. Designed ETL processes using SSIS to automate data migration and integration tasks.

Researched, developed, and maintained statistical reporting models in R, and developed R Shiny applications showcasing machine learning for business forecasting. Implemented DAX functions for efficient data visualization in Power BI, including charts and summaries to interpret findings for leadership.

Administered and analyzed links between customer attitude with user behavior and product usage data. Outlined and automated interactive KPI dashboards with sentiment scores in PowerBI.

Analysis of customer database using big query / SQL. Designed and implemented SSIS packages to automate data integration and migration tasks.

Implemented data exploration to analyze patterns and to select features using python SciPy. Built factor analysis and cluster analysis models using python SciPy to classify customers into different groups.

Used Pandas, NumPy, Seaborn, SciPy, Matplotlib in python for developing various machine learning algorithms. Designed and developed weekly, and monthly reports related to the marketing of clients using big query.

Performed Data analysis on many critical projects through which some of the critical business decisions were made. Developed logistic regression models using R programming and Python to predict employment response rates based on customer variables like demographics, interests, experience, and skill set.

Completed a Master's degree focusing on Information Technology. The curriculum likely covered advanced topics in IT, preparing for roles in data analysis and management.

Pursued an MBA, gaining knowledge in business management and strategy. This degree complements technical skills with a strong understanding of business operations.

Earned a Bachelor of Arts with honors in Business Management. This program provided a foundational understanding of business principles and management practices.