Nakshatra Devkar

Data Analytics

Pune 1+ yrs exp 87 · Excellent

About

B.E. AI & Data Science graduate (CGPA 8.45) with hands-on expertise in Power BI (DAX, Power Query M), Advanced Excel (Power Query, Pivot, openpyxl automation), SQL, and Tableau. Owns the full BI lifecycle — from star schema data modelling to KPI dashboards and executive-ready presentations. Built 6 projects delivering actionable insights from datasets up to 85,907 records, with proven ability to translate complex data into clear business narratives for senior stakeholders. Microsoft Power BI certified. Available immediately, based in Pune.

Skills & Expertise (57)

Power BI Service Intermediate

7.5/10

Years Exp

Power BI Desktop Intermediate

7.5/10

Years Exp

Tableau Intermediate

7.5/10

Years Exp

Advanced Excel Intermediate

6.5/10

Years Exp

ETL Intermediate

6.5/10

Years Exp

MySql Intermediate

6.5/10

Years Exp

Git Intermediate

6.5/10

Years Exp

Data Modelling Intermediate

6.5/10

Years Exp

Python Intermediate

6.5/10

Years Exp

DAX Intermediate

6.5/10

Years Exp

PowerPoint Seaborn Executive Presentations Stakeholder Reporting Business Requirement Translation Plotly Cross-Functional Collaboration Classification Computer Vision Regression NLP TF-IDF Sentiment Analysis CrewAI Gen AI AWS GitHub Databricks REST APIs Jupyter Notebook VS Code MySQL WorkBench LLMs SQLite KPI Cards Time intelligence Drill-throughs Looker Star Schema Power Query Pivot Tables Complex formulas Dashboards Automated Reporting OpenpyXL Matplotlib CTEs Window Functions RFM Segmentation Data Extraction Transformation KPI Tracking Trend Analysis Forecasting EDA Pandas NumPy

Work Experience

Data Analytics Intern

AVA Technology

Jan 2024 - Jan 2025

Owned the full BI reporting lifecycle across 4 client-facing projects — from data modelling and SQL extraction to Power BI/Tableau dashboards and executive-ready presentations translating insights into strategic recommendations. Built a binary ML model (79% ROC-AUC) on 85,907 records using Random Forest, NLP (TF-IDF, NLTK), and SMOTE; validated 3 business hypotheses at p < 0.05. Proactively identified 58% unfulfilled ride rate across 6,745 records via Python EDA, 25+ SQL queries, and Excel/Tableau dashboard — translated trend findings into 6 strategic recommendations projecting 42%→65% trip completion improvement. Merged 6 Fitbit datasets (940 records, 33 users); revealed 32% CDC step compliance and 16.5 hrs/day sedentary average; delivered 5 marketing recommendations. Designed star schema in MySQL, wrote 20 business queries (CTEs, Window Functions, RFM segmentation, MoM trends) on 9,800-row Superstore dataset.