Power Bi Data Analyst

AGRANSH SRIVASTAVA

***** ******* **** ******** ****, MD, 221042 571-***-**** *****************@*****.*** LinkedIn

SUMMARY

Business-focused Analyst with 2+ years of experience delivering data-driven insights using Excel (including Power Query), Power BI, and low-code SQL. Expertise in statistical analysis (R/SPSS), multivariate modeling, and Power Apps development to automate reporting and dashboards. Proven ability to translate ambiguous requests into testable hypotheses, manage project timelines, and partner with stakeholders to drive actionable insights.

.WORK EXPERIENCE

MOURITECH

Data Analyst May 2022 – Present

Data Collection & Preparation: Built and automated ETL pipelines in Python and Alteryx to gather, clean, and validate data from QAD systems, APIs, spreadsheets, and Teradata sources; implemented data quality checks and standardization rules in collaboration with data governance teams.

Data Analysis & Interpretation: Conducted EDA using Pandas and statistical methods to uncover patterns and anomalies in warrantyclaim workflows, reducing processing times by 20% and saving $200K annually.

Reporting & Visualization: Designed and maintained interactive dashboards and reports in Tableau and Power BI to present trends, forecasts, and KPI tracking; enabled stakeholders to make informed decisions through clear, concise data narratives.

Predictive Modeling & Stakeholder Engagement: Developed statistical and machine learning models in Python to forecast warranty claim volumes and rebate impacts; collaborated with cross-functional teams to validate solutions and integrate insights into strategic planning processes.

Stakeholder Collaboration & LAGBI Project: Led the LAGBI initiative at Stanley Black & Decker, extracting and consolidating tables from South American operations, and integrating rebate and warranty data into unified, audit-ready data marts.

Outdoor Data Consolidation: Consolidated outdoor operations datasets across regions to enhance cross-functional reporting and drive comprehensive performance analysis.

Tools & Technologies: SQL (Teradata, Snowflake), Python (Pandas, Scikit-learn), Alteryx, Tableau, Power BI, DBT Cloud, Azure Data Factory, Excel (VBA), Git, DAX

Engineered a Python/Scrapy-based ingestion pipeline integrated with Snowflake, maintaining a 99.8% pricing accuracy rate by comparing real-time menu data to ERP records.

Built SipBuddy, a conversational AI tool connected to OpenAI and Snowflake datasets to enable personalized recommendations and track hot-selling and aging inventory.

Designed metadata tagging and profiling logic to enrich Snowflake datasets used for product insights and performance monitoring.

Delivered functional documentation and best-practice guidance on data quality checks, scraping ethics, and Snowflake connector usage.

University of Maryland Baltimore County – Baltimore, MD

Teaching Fellow Jan 2023 – May 2023

Graded assignments and provided one-on-one coaching on best practices for data documentation and dashboard design.

PROJECT EXPERIENCE

Stanley Black and Decker Towson, MD

May 2023 – Present

Stakeholder Collaboration & LAGBI Project: Led the LAGBI initiative at Stanley Black & Decker, extracting and consolidating tables from South American operations, and integrating rebate and warranty data into unified, audit-ready data marts.

Outdoor Data Consolidation: Consolidated outdoor operations datasets across regions to enhance cross-functional reporting and drive comprehensive performance analysis.

Supported internal reviews of warranty claim flows, identifying high-cost anomalies and areas for control improvement.

Developed audit-friendly dashboards in Power BI for financial performance, warranty claim integrity, and operational effectiveness.

Documented ETL pipelines and implemented audit trail mechanisms for transactional data movement using snowflake and DBT cloud.

Mission Impact Dashboard

Developed a Streamlit application with automated data ingestion and audit log features to monitor KPIs for nonprofit initiatives.

Implemented cohort analysis to segment program participants and measure impact over time, visualized results in interactive reports.

Wildfire Risk Forecasting (Capstone)

Designed geospatial forecasting model in Python to predict wildfire risk; integrated outputs into Snowflake and presented via Tableau dashboards.

Performed statistical validation and sensitivity analysis; collaborated with stakeholders to refine data requirements and visualization layouts.

SKILLS

BI & Visualization: Power BI, Power Query, Power Apps, Tableau, Excel (PivotTables, VBA)

Data Processing: SQL (Snowflake, Teradata), Python (Pandas), Alteryx

Statistical Tools: R, SPSS; Multivariate Modeling, Hypothesis Testing

Project Management: Agile/Scrum, Requirements Gathering, Risk & Milestone Tracking

Collaboration & Versioning: Git, Cross-Functional Workshops

CERTIFICATIONS AND AWARDS

University of Maryland’s Dean’s list Award for excellence during spring semester 2022 and 2023 (GPA 3.7) and presidents list award for Fall 2024 (GPA 4.0)

EDUCATION

University of Maryland Baltimore County Baltimore, MD

Master’s in Data Science Graduation Date: May 2025

B.S. in Computer Science and Data Science with a Minor in Information Systems -Graduation Date: Jul 2024

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