Data Analyst SQL, Power BI, Python.

Jash Boghani

linkedin.com/in/jboghani** — ********@***.*** — 602-***-**** — Tempe, AZ

Education

W. P. Carey School of Business, Arizona State University May 2026 Bachelor of Science, Business Data Analytics / Supply Chain Management Tempe, United States

GPA: 3.69/4.00

Honors and Awards: Dean’s List, Kaplan International Scholar, New American University Scholarship ( 14,500) Work Experience

Business Intelligence & Data Pipeline Analyst Sep 2025 – Dec 2025 Stem Wine Company Tempe, United States

Architected an ETL pipeline in Python consolidating Vinosmith, QuickBooks, and Velocity data across 1,500+ SKUs – cleansing headers, deduplicating records, and producing a single source-of-truth fact table for downstream BI reporting.

Engineered invoice-level credit reconciliation logic (by invoice #, SKU, and customer) correcting overstated revenue across a 10M+ operation; built a 3-tier cost hierarchy (Laid-In FOB Velocity) to surface true realized return by SKU, supplier, and rep.

Delivered two Tableau dashboards with inventory aging alerts (45/60/90-day thresholds), at-risk SKU flagging, and a credit audit trail; authored documentation enabling non-technical managers to self-serve insights independently. Category Strategy Analyst Aug 2025 – Oct 2025

Vero Pizzeria Tempe, United States

Conducted supply market analysis for Vero Pizzeria’s pizza ingredient spend – executing PEST, Porter’s Five Forces, and portfolio analysis to identify sourcing risks, supplier concentration, and price seasonality patterns driving cost volatility.

Built a spend cube from invoice/PO data to surface 80/20 spend distribution; developed a supplier scorecard (cost, quality, reliability) visualized as a heat map and delivered KPI-backed sourcing recommendations to client management.

Translated analytical findings into a structured category strategy deck, presenting data-driven cost reduction opportunities and dual-sourcing recommendations directly to client stakeholders. Project Experience

Predictive Modeling for Hotel Revenue Optimization March 2025 – May 2025 Arizona State University Tempe, United States

Analyzed 36k+ booking records using Random Forest and Logistic Regression; engineered external features (events, weather) to achieve 0.89 ROC-AUC and reduce MAPE by 20%, improving forecast reliability for pricing decisions.

Designed and delivered Tableau pricing dashboards enabling the revenue team to evaluate 3x more pricing scenarios daily – translating model outputs into actionable business intelligence for non-technical stakeholders.

Performed cross-validation and hyperparameter tuning to compare model performance; documented feature importance rankings to communicate key demand drivers to business stakeholders. Stock Price Prediction January 2025 – March 2025

Arizona State University Tempe, United States

Built a scalable PySpark data pipeline on GCP Dataproc processing 1M+ rows; applied feature regularization and walk-forward cross-validation to reduce model overfitting by 31%.

Migrated model training from Colab to Dataproc, improving throughput 40% on large datasets; automated retraining cycles with Airflow to ensure consistent, scheduled model refreshes.

Engineered time-series features including rolling averages, momentum indicators, and volatility measures; evaluated LSTM and gradient boosting models using Sharpe ratio and directional accuracy as business-relevant metrics. Skills

Frameworks/Tools: SQL Power BI (DAX, Power Query/M) Tableau Excel (Advanced) Python Pandas NumPy scikit- learn PySpark GCP (BigQuery, Dataproc) Azure (Data Factory, Synapse, Databricks – basics) Spark SQL T-SQL Airflow Jupyter Notebook Agile/Scrum

Technical Skills: Data wrangling Statistical analysis Data modeling (star/snowflake) ETL/ELT Data validation/QA Dashboard development Business intelligence SQL optimization Predictive modeling Classification/regression Time-series forecasting Feature engineering Data storytelling Cloud data warehousing (BigQuery/Azure Synapse)

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