Mohammed‑Taqi Jalil
Summary
Data‑driven Computational Biology graduate with experience in data analysis, machine learning, and visualization. Specialized in Python, SQL, Tableau, and statistical modeling. Proven track record of delivering actionable insights through predictive modeling, ETL automation, and interactive dashboards.
Experience
Data Engineer Intern · SNH AI
Built Label Studio workflows for streamlined annotation for AI agents. Standardized heterogeneous XML to a unified golden dataset; validated via XSD. Aligned data prep with ML training across cross‑functional stakeholders.
Data Analyst Intern · JSoftUSA
Analyzed student data; insights contributed to 15% increase in platform adoption. Automated ETL with SQL; reduced manual reporting time by 30%. Developed Tableau dashboards; supported regression analysis for interventions.
Education
B.S., Biology (Computational) · The University of Texas at Austin
Coursework: Data Science, Regression Analysis, Biostatistics, Statistical Modeling, Genomics, Data Mining, Mathematical Statistics.
Technical Skills
Programming: Python, R, SQL
Libraries & Tools: Pandas, NumPy, Scikit-learn, XGBoost, DESeq2, ggplot2, tidyverse
Databases: MySQL, MS SQL Server
Visualization: Tableau, Power BI, Matplotlib, Plotly
Methodologies: EDA, Predictive Modeling, Regression, ETL, A/B Testing, Statistical Inference
Projects
Ambient Air Pollution Prediction
Built models (Random Forest, XGBoost, k‑NN, Lasso) to predict PM2.5 across the U.S.; performed EDA, feature selection, and cross‑validation using RMSE.
IntelliVest Investment Analytics Platform
Developed a comprehensive investment analytics platform with real-time market data integration, portfolio optimization algorithms, and interactive dashboards.
RNA‑Seq Gene Expression Analysis
Differential expression with DESeq2; normalization, QC, and log fold‑change; visualized results with PCA, volcano plots, and heatmaps.