VISHWAS GURAV · PORTFOLIO

ANALYTICS PORTFOLIO

Vishwas
Gurao

Data Analyst — Python · SQL · Power BI · Machine Learning
Turning raw data into clear, actionable insights.

I build end-to-end data analytics projects using Python, SQL, and Power BI — from cybercrime intelligence dashboards for Kolhapur District Police to NLP sentiment classifiers and supply chain optimisation. Open to Data Analyst and Data Science roles across India.

Python SQL Power BI EDA Pandas Machine Learning Data Visualisation Jupyter
Download Resume View Projects →

Gadlegaon, Karnataka, India  ·  Immediate Joiner  ·  Open to Relocation

20,000+
CYBERCRIME COMPLAINTS
Analyzed (2019–2025)
4M+
UBER TRIP RECORDS
Demand forecasting
6+
ANALYTICS PROJECTS
End-to-end delivery
80.6%
ONLINE FINANCIAL FRAUD
Primary crime category
About

Analyst by nature,
Developer by practice

I'm Vishwas Gurao, a Data Analyst and MCA (Data Science) student at Shivaji University, Kolhapur. I enjoy the process of turning messy datasets into structured narratives — whether that's mapping cybercrime patterns across police divisions or forecasting urban transportation demand.

My work spans exploratory data analysis, statistical modelling, and data visualisation. I've worked on projects in collaboration with institutional stakeholders, which has given me a practical understanding of how analytical findings translate into operational decisions.

Based in Kolhapur, Maharashtra, I focus on structured EDA, business reporting, and insight communication. My core stack is Python (Pandas, Seaborn, Matplotlib), SQL, and Power BI — translating complex data into clear dashboards and reports for both technical and non-technical audiences.

GitHub Repositories → LinkedIn Projects →
EDUCATION
MCA – Data Science
LOCATION
Gadlegaon, Karnataka
STATUS
Immediate Joiner
AVAILABILITY
Open to Relocation
SHIFTS
Comfortable with Rotational
LANGUAGES
English · Marathi · Hindi
Background

Experience & Education — Vishwas Gurao

Work Experience

Data Science Intern

Dec 2025 – Mar 2026
Unified Mentor Private Limited
  • Performed EDA and visualisation on structured datasets using Python and Jupyter Notebook
  • Developed charts and analytical summaries using Matplotlib and Seaborn
  • Prepared structured project documentation and reporting workflows
  • Executed data cleaning, validation, and trend identification tasks

Analytical Collaboration

2025
Kolhapur District Police · Cyber Crime Cell
  • Analyzed 20,000+ cybercrime records using Python and Pandas
  • Performed geospatial mapping across 30+ police divisions
  • Produced sanitized analytical summaries and trend visualisations
Restricted · Confidential Data

Education

MCA – Data Science

2024 – 2026
Shivaji University, Kolhapur
  • Master of Computer Applications with Data Science specialisation
  • Focus on statistical analysis, machine learning, and Python programming
  • Active project work through Avishkar Research Competition

Academic & Technical Engagements

  • Avishkar Research Competition — data-oriented project presentations
  • GitHub-based project management and version control
  • Python analytical projects across web-oriented and data domains
Projects

Data Analytics & Data Science Projects

End-to-end data analytics projects built with Python, SQL, Power BI, and machine learning — spanning cybercrime intelligence, demand forecasting, NLP sentiment analysis, and supply chain analytics.

Data Analyst View All on LinkedIn →
Daily Uber trips 7-day smoothed trend
4 CHARTS
Unified Mentor
4M+ Records

Uber Demand Forecasting Analysis

Statistical analysis of 4M+ Uber trip records to identify demand fluctuations, peak-usage patterns, and day-of-week behavioural trends. The study applies 7-day smoothing to reduce noise and reveal underlying demand seasonality, revealing a 16.4% month-on-month growth rate.

Saturday peaks at 13,913 average daily trips; Monday lowest at 9,662
16.4% month-on-month growth (Jan → Feb 2015)
7-day rolling average applied for trend smoothing
Python Pandas Statistical Analysis Time Series Matplotlib Seaborn
GitHub → LinkedIn
Attrition by job role — Sales Representative highest at 39.8%
6 CHARTS
Unified Mentor
1,470 Records

Employee Attrition Analysis

Exploratory data analysis on 1,470 employee records from the IBM HR Analytics dataset. The study identifies workforce attrition patterns by job role, job satisfaction level, and departmental distribution — providing a data-driven view of retention risk factors and behavioural indicators.

Sales Representatives show highest attrition: 39.8% turnover rate
Lower job satisfaction (score 1) correlates with higher attrition
Research Directors show lowest attrition: 2.5%
Python Pandas EDA Seaborn Matplotlib
GitHub → LinkedIn
Revenue, Manufacturing Cost and Profit comparison by product type
7 CHARTS
Unified Mentor
EDA + ML

Supply Chain Analytics

Analytical assessment of supply chain datasets covering revenue distribution by location, inventory stock vs. order patterns, and product-level profitability. Mumbai and Kolkata lead revenue generation; skincare shows highest total revenue at 241,628.

Skincare: highest revenue at 241,628
Mumbai leads location revenue at 137,755
Python EDA Pandas ML Seaborn
GitHub →
Label distribution across 20 financial news categories
5 CHARTS
Unified Mentor
NLP

Financial Sentiment Analysis

Text classification of financial Twitter data using NLP techniques including Linear SVM. 20 financial news categories classified from 17,000+ tweets, with Company / Product News dominating at 3,545 instances. Confusion matrix demonstrates strong diagonal performance.

20 financial news categories classified
Linear SVM as primary classification model
Python NLP Scikit-learn SVM Text Analysis
GitHub →
Top 10 laptop companies by average price range
9 CHARTS
Unified Mentor
Regression · ML

Laptop Price Prediction

Machine learning regression model to predict laptop prices based on hardware specifications including RAM, brand, processor type, and storage configuration. Price range analysis across 10 major manufacturers reveals MSI and Apple commanding premium price segments.

64GB RAM configurations reach €3,975 price point
Apple and MSI identified as premium-tier brands
Python Scikit-learn Regression EDA Pandas
GitHub →
Methodology

Research & Methodology

A consistent analytical workflow applied across all projects — from data acquisition through to structured reporting.

Data Acquisition & Scoping

Identifying and sourcing structured datasets from institutional records, public repositories, and domain-specific platforms. Scope definition covers time range, geographic boundaries, and analytical objectives.

Kaggle Institutional Data GitHub Datasets

Data Cleaning & Validation

Systematic data cleaning using Pandas — handling missing values, removing duplicates, standardising formats, and validating data integrity before analysis begins.

Pandas NumPy Data Validation

Exploratory Data Analysis

Statistical profiling, distribution analysis, correlation mapping, and outlier detection. EDA phase drives hypothesis formation and narrows analytical focus areas.

Descriptive Stats Correlation Outlier Detection

Visualisation & Reporting

Translating analytical findings into clear visual narratives using Seaborn and Matplotlib. Chart selection prioritises interpretability for both technical and non-technical stakeholders.

Seaborn Matplotlib Heatmaps

Predictive Modelling

Building and evaluating ML models including regression, classification, and NLP pipelines. Model selection is driven by data structure and business objective.

Scikit-learn SVM Regression NLP

Documentation & Delivery

Structured project notebooks with clear markdown commentary, interpretation sections, and insight summaries. All repositories maintained on GitHub with organised file structure.

Jupyter Notebook GitHub Markdown

Tools, Libraries & Frameworks

Languages

  • Python 3.x
  • SQL (basic)
  • Markdown

Libraries

  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Scikit-learn

Tools

  • Jupyter Notebook
  • VS Code
  • GitHub
  • Excel

Techniques

  • EDA
  • Time Series Analysis
  • Geospatial Analysis
  • NLP / Text Classification
  • Regression Modelling
Skills

Technical Skills

Core analytical and programming skills applied across real-world data projects.

Languages & Libraries

Python (Pandas, NumPy) Advanced
Matplotlib / Seaborn Advanced
Scikit-learn Intermediate
SQL (Querying) Intermediate

Analysis & Methodology

Exploratory Data Analysis Advanced
Statistical Analysis Intermediate
Data Cleaning & Validation Advanced
Reporting & Documentation Advanced

Machine Learning & Tools

Jupyter Notebook Advanced
GitHub & Version Control Intermediate
Regression / Classification Intermediate
NLP / Text Classification Intermediate

Soft Skills

Analytical Thinking Problem Solving Attention to Detail Communication Team Collaboration Documentation Presentation
Credentials

Certifications & Education

Certifications

Data Analytics Job Simulation

Deloitte Australia · Forage · 2025

Data Science

Cisco · 2025

Cybersecurity Analyst Job Simulation

Tata Group · Forage · 2025

Education

Shivaji University, Kolhapur

Master of Computer Applications (MCA) — Data Science

2024 – 2026 · Maharashtra, India

Python Machine Learning Statistics Data Science

Avishkar Research Competition

Analytical project presentations · 2025

Get in Touch

Open to opportunities.
Let's talk.

I'm actively looking for Data Analyst and Data Science Intern roles. If you're working on an interesting analytics problem or have a role that fits, I'd love to connect.

Email

vishwasforjobhunt@gmail.com

LinkedIn

linkedin.com/in/vishwas-gurav

GitHub

github.com/VishwasGurao
DATA ANALYST MODE ACTIVE

Download My Resume

Tailored for Data Analyst roles — highlights EDA, data visualisation, reporting, and project experience with Python and analytical tools.

Download Resume
Notice Period Immediate Joiner
Relocation Open
Rotational Shifts Comfortable