Data Analyst & BI Cloud ETL Pipelines

ABDUL HADI

Data Analyst Business Intelligence Cloud & ETL Pipelines

320-***-**** ******.****.**@*****.*** linkedin.com/in/abdul-h-mohammed MN

PROFESSIONAL SUMMARY

Data Analyst with 3+ years of hands-on experience turning complex financial and operational datasets into executive-ready dashboards, automated pipelines, and predictive models. Specialized in banking analytics — including fraud detection, credit risk, and loan portfolio performance — using SQL, Python, Power BI, Snowflake, and AWS. Known for building reporting infrastructure that replaces hours of manual work with reliable, scheduled automation. M.S. in Information Assurance (2025). Actively seeking full-time Data Analyst roles. Open to immediate start.

CORE TECHNICAL SKILLS

Programming & Query Languages: SQL (Advanced SQL, CTEs, Window Functions, Stored Procedures), Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Plotly), VBA

Cloud & Database Technologies: AWS (S3, Redshift, Athena, Lambda, Glue), Snowflake, Azure Data Factory, SQL Server, Oracle, MySQL, dbt

ETL & Data Engineering: Alteryx, Informatica, PySpark, Hadoop, Power Query, ETL Development, Star Schema, Dimensional Modeling, Data Warehousing

Business Intelligence & Reporting: Power BI (DAX, Power Query), Tableau, Looker, Advanced Excel, KPI Dashboard Design, A/B Testing, Data Visualization

Machine Learning & AI: Scikit-learn (Regression, Decision Trees, Random Forests, KNN, K-Means, PCA), AutoML, Azure Machine Learning, OpenAI API

Tools & Methodologies: Data Governance, Data Quality Management, Agile, SDLC, JIRA, Confluence, Git, GitHub, Requirements Gathering, Business Analysis, Documentation, Stakeholder Management

PROFESSIONAL EXPERIENCE

Data Analyst · Ally Financial · Detroit, MI

Aug 2023 – Present

•Wrote and optimized complex SQL queries — CTEs, window functions, and stored procedures — to analyze customer transactions, detect fraud patterns, and measure credit risk metrics; cut report generation time by 40%.

•Designed and published Power BI dashboards used by C-suite and department heads to monitor loan performance, delinquency rates, and portfolio risk in real time.

•Built Python + Snowflake pipelines replacing daily and weekly manual reporting; reports now run automatically on schedule with zero human intervention, saving ~15 hours/week.

•Created dimensional data models (Star Schema) in Snowflake to consolidate data from CRM, loan servicing, and payment platforms into a single unified analytics layer.

•Maintained 99%+ data accuracy through rigorous ETL validation, data profiling, and cleansing routines applied to critical financial datasets.

•Developed Scikit-learn models to predict loan default probabilities; used AutoML to shortlist best-performing algorithms and tune hyperparameters.

•Implemented anomaly detection logic to flag suspicious transactions in near real-time; collaborated with Risk and Compliance for regulatory reporting.

•Integrated OpenAI API to generate automated plain-language narrative insights inside executive dashboards, reducing analyst interpretation effort.

Project: Loan Default Prediction & Credit Risk Scoring Engine Tools: Python, Scikit-learn, AutoML, Snowflake, Power BI

•Built an end-to-end ML pipeline to predict loan default probability across Ally's consumer lending portfolio using 3 years of historical repayment, income, and behavioral data.

•Trained and evaluated 6 classification models (Logistic Regression, Random Forest, XGBoost, KNN, Decision Tree, SVM); Random Forest + AutoML tuning achieved 87% AUC-ROC.

Project: Enterprise Fraud Detection & Anomaly Monitoring System Tools: Python, SQL, AWS Glue, Snowflake, Power BI, OpenAI API

•Designed and implemented an automated anomaly detection system to identify suspicious transactions across Ally's payment and loan servicing platforms in near real-time.

•Built Python-based statistical models (Z-score + Isolation Forest) to detect outlier transaction amounts, unusual access patterns, and velocity anomalies across 2M+ monthly records.

•Integrated OpenAI API to auto-generate plain-English alert summaries for the Compliance team, replacing 4 hours/week of manual investigation documentation.

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Data Analyst · Tally Solutions · Remote, India

Apr 2020 – Oct 2022

•Owned end-to-end reporting for the enterprise BAU team — raw data extraction through final stakeholder delivery across sales, operations, and finance verticals.

•Wrote SQL queries and stored procedures to extract, filter, and mine complex operational and sales datasets for ad hoc and scheduled analysis.

•Automated Excel-based reporting workflows using Python (Pandas, NumPy) and VBA macros, saving 20+ hours of manual effort per week across the reporting team.

•Built and maintained Tableau dashboards tracking sales performance, operational KPIs, and product metrics for senior management.

•Designed star schema data models and ETL workflows in Alteryx and Informatica, improving data reliability and reducing pipeline failures.

•Applied linear and logistic regression models to build predictive sales forecasting tools used by the risk management team.

Project: Sales Forecasting & Revenue Intelligence Dashboard Tools: Python, SQL, Alteryx, Tableau, Excel

•Built a sales forecasting model using 2 years of historical transaction data to predict weekly and monthly revenue across 8 product categories for Tally's enterprise client base.

•Applied linear regression and time-series analysis (moving averages + seasonal decomposition) to generate forecasts with 91% accuracy at the 30-day horizon.

•Automated the full data refresh pipeline using Alteryx workflows and Python scripts; Tableau dashboard updated daily without any manual intervention.

Project: ETL Automation & Operational Reporting Pipeline Rebuild Tools: Python, SQL, Informatica, Alteryx, Tableau, VBA

•Identified 14 recurring manual reports consuming 20+ hours/week across the BAU team; redesigned each as an automated ETL pipeline with scheduled delivery.

•Built Informatica and Alteryx workflows to extract data from 5 source systems, apply transformation rules, and load clean data into the central reporting warehouse.

EDUCATION

Master of Science — Information Assurance St. Cloud State University, St. Cloud, MN

May 2025

KEY ACHIEVEMENTS

•40% reduction in SQL report generation time at Ally Financial through query optimization and cloud migration.

•22+ hours/week saved at Tally Solutions through Python, Alteryx, and VBA reporting automation.

•99%+ data accuracy maintained consistently across two enterprise organizations.

•Loan default prediction model achieving 87% AUC-ROC, estimated to reduce credit exposure by $2.1M annually.

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