Hello, I'm Tejas Bhanarkar šŸ‘‹

Data Analyst |

Just a Data Nerd Making Sense of Chaos.

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Tejas Bhanarkar

About Me

I'm Tejas, a Experienced Data Analyst with hands-on expertise in Power BI, SQL Querying, and Microsoft Excel. Skilled in transforming complex data into actionable insights to support strategic decision making. Proven ability to automate workflows, visualize trends, and enhance business efficiency. Passionate about applying data-driven solutions to business challenges and eager to contribute to innovative, high-impact projects.

Skills & Technologies

Power BI Tableau Excel SQL Python Microsoft SQL Server Mongo DB Data Visualization Statistics & Optimization AI & ML AWS & Azure

Education

Msc In Data Analytics = {
College: 'National College of Ireland',
Archieved: 'First Class Honours 1:1',
Year: '2024 - 2025',
};
B.E. In Information Technology = {
College: 'St.Vincent Pallotti College',
Archieved: 'SGPA 9.09/10',
Year: '2018 - 2022',
};

Experience

Associate Data Analyst | INFOCEPTS TECHNOLOGY

Nagpur, Maharashtra, India ā€¢ 2022 ā€“ 2023

  • Collaborated with Talen Energy to design and implement Power BI dashboards focused on energy consumption analysis and Bitcoin mining operations, delivering actionable insights for performance and sustainability tracking.
  • Developed responsive mobile and tablet versions of dashboards, increasing cross-device accessibility and boosting user engagement by 37% among field teams and executives.
  • Performed data cleaning, validation, and SQL optimization on backend data workflows by developing and tuning over 47 complex SQL queries, ensuring high data accuracy and enabling real-time dashboard updates.
  • Built an end-to-end automated user management system in Power BI to streamline role assignments and access controls, reducing manual effort by 76% and ensuring full audit traceability.
  • Key Achievement: Played a vital role in building a dynamic and self-refreshing enterprise analytics ecosystem by integrating SQL-driven automation, leading to a measurable uplift in executive responsiveness and data normalization across departments.

Research Intern | IIITH

Hyderabad, Telangana, India ā€¢ 2020 ā€“ 2021

  • Conducted in-depth analysis of multilingual linguistic datasets to identify structural patterns and improve semantic parsing performance across languages.
  • Performed large-scale data preprocessing, cleaning, and annotation to improve data quality and model reliability, while conducting statistical and error analysis to identify performance gaps and drive improvements.
  • Collaborated with cross-functional teams to develop and test data-backed optimization strategies, resulting in a 15ā€“20% increase in semantic parsing accuracy.
  • Designed multilingual evaluation frameworks and performance metrics for delivering analytical insights that drove iterative improvements in parsing algorithms and overall system robustness.
  • Key Achievement: Leveraged structured data analysis and performance evaluation techniques to drive measurable improvements in multilingual NLP model accuracy and scalability.

My Projects

BI & CRM Analytics System

BI & CRM Analytics System

Built Salesforce CRM modules and Tableau dashboards to simulate customer strategies for Deliveroo. Performed sentiment analysis and user segmentation on Zomato and Swiggy datasets using TextBlob and segmentation to optimize loyalty campaigns.

Python SAP Power BI MySQL & MongoDB
Case Study GitHub
Face Recognition AI Assistant

Face Recognition AI Assistant

Developed a portable AI assistant featuring secure facial recognition login and real-time authentication implemented using OpenCV and LBPH. Integrated Google Gemini AI and pyttsx3 for voice-enabled conversations, deployed as a standalone .exe on USB.

OpenCV Python LBPH Google Gemini
Installation Guide GitHub
Attrition Risk Analyzer

Attrition Risk Analyzer

Built an XGBoost based predictive analytics model achieving 92% accuracy to forecast employee attrition and identify key organizational risk factors influencing turnover. Designed a Gradio web app for real-time HR engagement and deployed on Hugging Face.

XGBoost Python Gradio Scikit-Learn
Live App GitHub
AquaSence AI System

AquaSence AI System

Engineered a DL based water quality prediction system using ResNet model, achieving 71.8% accuracy. Incorporated Google Gemini AI for natural language diagnostics and deployed using a Gradio interface.

ResNet TensorFlow / PyTorch Gradio Google Gemini
Live App GitHub

Get In Touch

Interested in Collaborating on Data Analytics, BI Dashboards, or Machine Learning Projects? Iā€™m Always Open to Discussing Opportunities where Data can Drive Real Business Impact.

tejas.bhanarkar101@gmail.com
+91 9325635070
India