Power BI Data Analyst

ABHRAJIT DAS

Jersey City, NJ ***** 929-***-**** ********.********@*****.*** Portfolio GitHub LinkedIn PROFESSIONAL SUMMARY

Data Analyst & Power BI Developer with a strong foundation in SQL, Python, and cloud-based data engineering. Created dashboards, accelerated ETL workflows by 25%, and deployed ML models with up to 90% accuracy. Architected Azure Synapse and Data Factory solutions, driving 30% faster decision-making across healthcare and product domains. TECHNICAL SKILLS & CERTIFICATIONS

Certifications: AZ 900 (Microsoft Azure Certified, 2025) PL 300 (Microsoft Power BI Certified 2025) IBM Data Science (2024) Programming Languages & Libraries: Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn) R (Beginner) Database Management: MYSQL Microsoft SQL Server PostgreSQL Hadoop Microsoft TSQL Data Visualization Tools: Power BI Tableau MATLAB Google Analytics MS Excel Machine Learning Algorithms: Logistic Regression Natural Language Processing XGBoost KNN Random Forest LSTM Cloud Services: Azure Data factory Azure Synapse Azure Blob Storage Azure Active Directory EXPERIENCE

MyMedGlobal, California Full-time Data Analyst and Power BI Developer March 2025 – Present

• Spearheaded development of 25+ high-impact end-to-end Power BI dashboards using DAX and Power Query, enabling executives to make data-driven decisions that improved operational efficiency.

• Orchestrated and optimized 20+ complex data pipelines with Microsoft Fabric Dataflow Gen2 and Lakehouse, leveraging CTEs, JOINs, and window functions to reduce data refresh times by 30% and boost data models reliability.

• Integrated Power BI with Azure Synapse, Databricks, and Snowflake; automated reporting workflows with Power Automate, driving 25% faster data delivery in a fast-paced Scrum environment. V2 Technologies, India Intern Business Intelligence Developer May 2024 – July 2024

• Delivered 20+ robust Power BI dashboards using Microsoft Fabric and applying advanced DAX and SQL techniques to accelerate insights by 30%, directly supporting business growth.

• Collaborated within Scrum teams to automate ETL workflows and streamline data integration from Azure, Databricks, and Snowflake, improving data accuracy and retrieval speed by 25%. Open-talk.co (Formerly findhope.in), India Full-time Co-Founder & Data Analyst April 2018 – July 2022

• Engineered Power BI dashboards and Excel-based audits for 8,000+ global users, uncovering engagement patterns and statistics that led to a 20% user retention increase and a 25% improvement in operational efficiency.

• Directed 5+ end-to-end analytics projects using Agile, delivering 10+ advanced data visualizations with drill-down insights, driving stakeholder alignment and measurable reductions in user burnout. PROJECTS

Atlas Labs: Workforce Insights & Attrition Analysis in Power BI [Link] January 2025 – March 2025

• Developed a multi-page Power BI HR analytics suite using 3+ data tables and 20+ advanced DAX measures to analyze attrition, performance trends, and workforce diversity.

• Created real-time KPIs, drill-through reports, and conditional formatting to drive data-informed HR decisions, improving leadership visibility and reducing churn risk detection time by 35%.

• Implemented 10+ bookmarks and 6 slicer-driven filters across 4 dashboard pages, boosting interactivity and increasing user accessibility and engagement by 40%.

Sentiment Analysis and NLP Classification on Taylor Swift's Lyrics Dataset [Link] September 2024 – December 2024

• Conducted EDA and data visualizations using NLP techniques, including sentiment trends and word frequency analysis revealing a 35% rise in positive sentiment in recent albums and recurring themes of "love" and "time".

• Built classification models, including SVM, Naive Bayes, Logistic Regression, LSTM and Random Forest achieving up to 90% accuracy in sentiment prediction analysis.

Top 500 Football Players: Insights via Data Analysis, Visualization, and Machine Learning [Link] January 2023 - May 2023

• Leveraged Pandas, NumPy and Seaborn to conduct a comprehensive analysis of a dataset containing 500 football players, employing data filtering techniques to refine the dataset and extract player-wise insights.

• Applied Machine Learning algorithms, including linear and logistic regression & K-means clustering, using scikit-learn to forecast out how many matches a player will need to play to score 100 goals. RESEARCH WORK & PUBLICATION

Predicting COVID-19 Cases using ARIMA, Prophet, LSTM & Data Analysis Using Power BI (Springer Publications) July 2024 Lecture Notes in Networks and Systems, Vol. 1, Springer Singapore, 2025, pp. 147-161. DOI: 10.1007/978-***-**-****-6 EDUCATION

Pace University, New York, NY — MS in Data Science Jan 2023 – Dec 2024 National Institute of Technology Agartala, India — B. Tech in Electrical Engineering July 2017 – May 2021

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