Muhammad Bilal Nasir
Austin, Texas Area
MS Data Science | Advance Analytics | AI | Machine Learning | Strategic Management
Graduate Assistant at Texas Tech University
Contact
MS Data Science | Advance Analytics | AI | Machine Learning | Strategic Management
Graduate Assistant at Texas Tech University
ContactData provides us information which is in-turn observed as knowledge. My challenge is to extract wisdom from knowledge. Having 11 years of work experience, from multiple industries and business domains, using my strong skills in data mining, advance statistical analysis, I can provide valuable data driven insights for business decision making. • Real Estate Market Price predictions: Multivariate analysis (PCA, factor analysis, model-based clustering, regression) on house features, prices and dependent variable. • Supply Chain-Backordering Optimization: Recommended inventory optimizations after outliers/anomaly analysis, predictive (Decision Tree), prescriptive analysis, qq-plots, normality tests on Kaggle Data set using Python, and R. • Blood Donor Prediction using Logistic Regression: Forecasted blood donation by donors, using Logistic Regression models and log transform models, multicollinearity, and residual analysis on datadriven.org competition using R. • Datawarehouse Design (OLAP): Designed star schemas for storing retails sales data with NoSQL (mongo DB). • Retail Sale Predictions using Weather Feeds: Wrote queries (SQL) for improved sales/inventory and price planning by designing and developing an OTLP database in SQL Server and used weather and holiday sales data. • Time Series Forecasting and Decomposition: predicted consumption of crude oil/gas in USA for future seasons, by moving average, STL decomposition for components trend/cycle, seasonality, error, de-trended data, using R (fpp). • Time Series and Regression on Dengue Disease Spread Prediction: forecasted total cases (patients) with 95% Prediction intervals, using decomposition, exponential smoothing, STL models, ARIMA models with R fpp package.
Trained high school teachers of Lubbock county on data science and its applications in cybersecurity as one of the grad student teacher trainers who worked on the national science foundation (NSF)-funded project (RET Site: Applied Data Science for Cyber Security).
Worked as an intern at United Super Markets, Albertsons in collaboration with Texas Tech Rawls college of business. Wrote SQL queries for data extraction for analytical model and transfer of master data to Texas Tech University for research collaboration purposes.
Retail Analytics: • Performed exploratory factor analysis and customer segmentation on product purchase spending, recency counts and products categories purchase.
• Performed customer segmentation on customer demographics psychometric variables using k-means clustering and using R and CRISP-DM process to provide management with actionable insight in form of visualizations.