Fresher Data Analyst - Python, SQL, Power BI

Nayan Jikar

+91-957******* # **********@*****.*** ï LinkedIn § GitHub + Wardha, Maharashtra Professional Summary

Fresher Data Analyst (B.Tech AI & ML, April 2026) with internship experience in FinTech and web development, delivering data-driven decision making solutions using Python, SQL, and Power BI. Skilled in end-to-end analytics—data pipeline development, data governance, EDA, business intelligence dashboards, KPI reporting, and data storytelling. 2nd Prize winner at MIT-WPU Hackathon; IBM-certified in Data Science and Machine Learning.

Skills

Core Analytics: Python, SQL (Joins, CTEs, Window Functions), Excel (Pivot Tables, VLOOKUP, open- pyxl)

Data Analysis & EDA: Pandas, NumPy, Data Cleaning, Feature Engineering, Root Cause Analysis, Trend Anal- ysis

Business Intelligence: Power BI, Tableau, DAX, Matplotlib, Seaborn, Dashboard Building, KPI Reporting, Data Storytelling

Business Reporting: MIS Reporting, Data Pipeline Development, Data Governance, Operational Tracking, P&L Analysis

Stakeholder Mgmt: Data-Driven Decision Making, Cross-functional Communication, Insight Presentation Statistics: Probability, Hypothesis Testing, A/B Testing Machine Learning: Scikit-learn, XGBoost, Regression, Classification, Predictive Modeling Databases: MySQL, MongoDB

Additional: TensorFlow, PyTorch, LangChain, HuggingFace, Docker, MLflow, Flask, FastAPI, GitHub

Experience

AI and Data Science Consultant Intern Jun 2025 – Feb 2026 Rubixe.AI, Bangalore – Hybrid Python, SQL, Pandas, Power BI, Machine Learning

– Contributed to a live FinTech analytics project — built and maintained data pipelines; performed end-to-end data cleaning, preprocessing, and validation across large-scale datasets to ensure data governance and pipeline-ready quality.

– Conducted EDA, root cause analysis, and trend analysis aligned with revenue and risk objectives; findings enabled data-driven decision making for operational and financial KPIs.

– Developed business intelligence dashboards and structured business reports in Power BI; communicated insights to stakeholders through data storytelling, supporting stakeholder management across business and technical teams. Python Developer Intern Jul 2024 – Oct 2024

Arohi Software, Pune – Remote Python, Flask, HTML, CSS, SQL

– Developed and deployed a Flask-based web application with modular backend routing, RESTful API endpoints, and Jinja2 templating; structured codebase across multiple blueprints to improve maintainability and scalability.

– Designed and implemented SQL database schemas with normalized table structures for efficient data storage and retrieval; wrote optimized queries reducing redundant data fetches and improving backend response consistency.

– Debugged and refactored Python backend logic, resolving critical application errors and improving code reliability; collaborated on end-to-end testing of API routes to ensure stable data flow between frontend and database. Awards & Certifications

• MIT-WPU Medico Engino Hackathon (2024): 2nd Prize — engineered a portable dialysis machine prototype using acrylic fabrication and a semipermeable membrane, in collaboration with Dassault Syst`emes.

• IBM Machine Learning Professional Certificate (Coursera, 2024): Supervised & unsupervised learning, model evaluation, and Python-based ML workflows.

• IBM Data Science Professional Certificate (Coursera, 2024): Data analysis, visualization, SQL, and applied machine learning through real-world projects.

Projects

Sales & Business Performance Analytics – E-Commerce Python, SQL, Power BI, Scikit-learn, Excel GitHub

– Designed an end-to-end data pipeline processing 100K+ orders across 9 relational tables; built master analytics dataset

(11,368 rows, 43 columns) using SQL joins, CTEs, and window functions following data governance best practices.

– Performed trend analysis identifying top 3 categories contributing 17% of GMV; built 4-page business intelligence dashboard in Power BI with 15+ KPIs; root cause analysis revealed 71.3% late deliveries as primary driver of customer dissatisfaction.

– Developed Random Forest classifier (78% accuracy) for late-delivery risk; automated monthly MIS reports via openpyxl; data storytelling report showed repeat buyers carry 2.4 higher lifetime value, enabling data-driven decision making for retention strategy.

Diabetic Readmission Prediction – Healthcare Analytics Python, XGBoost, Scikit-learn, SMOTE GitHub

– Built a data pipeline for real-world healthcare data — missing value treatment, categorical encoding, and SMOTE-based class-imbalance handling — enforcing data governance standards throughout preprocessing.

– Trained XGBoost model achieving 79% accuracy and AUC-ROC: 0.8761, outperforming baselines (74–75%); trend analysis of feature importances guided clinical decision support insights for stakeholder reporting.

– Designed a privacy-preserving federated architecture enabling multi-site hospital analysis without sharing raw patient data, aligned with HIPAA-analogous data governance standards. Education

Faculty of Engineering & Technology, DMIHER (DU) 2022 – 2026 B.Tech in Artificial Intelligence & Machine Learning Wardha, Maharashtra Dr. B.R. Ambedkar Jr. College 2021 – 2022

HSC Hinganghat, Maharashtra

Adarsh Vidyalaya 2019 – 2020

SSC Sakhara, Maharashtra

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