Available for opportunities

Ishant
Aneja

Data Analyst & Python Developer

Data Analyst and Python Developer with hands-on experience in data extraction, cleaning, analysis, and visualization using Python, SQL, Pandas, NumPy, and Matplotlib. Skilled in building REST APIs, backend systems, and ETL pipelines with MongoDB, PostgreSQL, and SQL. Proficient in MS Excel, Power BI, and Tableau for turning raw data into actionable business insights. Strong foundation in exploratory data analysis (EDA), data manipulation, and dashboard/report development.

Projects Built

Certifications

Years Coding

Technologies

Python SQL Power BI & Tableau ETL Pipelines Machine Learning Databases & APIs

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about.md

Who I am

I'm a Data Analyst and Python Developer based in Gurugram, India, currently pursuing my MCA at K.R. Mangalam University. My work bridges analytical inquiry and software engineering — extracting, cleaning, and modeling data to turn complex metrics into actionable business insights.

My toolkit spans the complete data lifecycle: hands-on experience in raw data extraction and wrangling using Python, Pandas, and NumPy, exploratory analysis and charting with Matplotlib, and interactive dashboards in Power BI, Tableau, and MS Excel. On the backend and data engineering side, I design scheduled ETL pipelines, integrated PostgreSQL databases using SQLAlchemy, write complex SQL queries using window functions and subqueries, and build REST APIs with MongoDB and SQL.

I also apply machine learning fundamentals with Scikit-learn, building time-series regression models and implementing financial risk analytics including Value at Risk (VaR), Expected Shortfall, and strategy backtesting.

Data Analytics & EDA

Data cleaning, manipulation, EDA, and statistical visualization.

ETL & Databases

Automated pipelines, PostgreSQL, MongoDB, SQL, and REST APIs.

BI & Reporting

Power BI, Tableau, and MS Excel dashboards for business decisions.

ML & Risk Analytics

Scikit-learn, time-series forecasting, VaR, and backtesting.

skills.json

Technical stack

Swipe left or right to switch skill categories

Data Analysis & Visualization

Data Cleaning & ManipulationAdvanced

Exploratory Data Analysis (EDA)Advanced

Data Extraction & ETL PipelinesAdvanced

Power BI (Dashboards & KPIs)Advanced

Tableau Visual AnalyticsIntermediate

MS Excel (Formulas, Pivot Tables, Modeling)Advanced

Data Visualization (Matplotlib)Advanced

Data Cleaning Data Manipulation Data Extraction Exploratory Data Analysis (EDA) Pandas NumPy Matplotlib Power BI Tableau MS Excel

Programming Languages & Core

PythonAdvanced

SQLAdvanced

JavaScriptIntermediate

PandasAdvanced

NumPyAdvanced

MatplotlibIntermediate

Python SQL JavaScript Pandas NumPy Matplotlib

Databases & Backend Systems

SQL (Joins, Aggregations, Window Functions, Subqueries)Advanced

PostgreSQLAdvanced

MongoDB (Aggregation Pipelines)Advanced

SQLAlchemy (ORM & Database Integration)Intermediate

REST APIs (Design, Validation, Performance)Advanced

WebSockets & Real-time ArchitectureIntermediate

PostgreSQL MongoDB SQL Window Functions Subqueries Aggregations Joins SQLAlchemy REST APIs WebSockets

Tools & Platforms

Git & GitHub (Version Control)Advanced

GitHub Actions (CI/CD & ETL Automation)Advanced

SQLAlchemy (ORM & Database Pipelines)Intermediate

Scikit-learn (Machine Learning & Modeling)Intermediate

Financial & Market APIs (yFinance, Binance)Advanced

Git GitHub GitHub Actions SQLAlchemy Scikit-learn yFinance API Binance API Power BI Tableau MS Excel VS Code Postman

AI Tools & Concepts

AI & Generative AI Tools

ChatGPT Claude Google Gemini GitHub Copilot Scikit-learn

REST APIsAdvanced

ETL PipelinesAdvanced

Data Structures & Algorithms (DSA)Intermediate

Machine Learning FundamentalsIntermediate

Financial Risk Analytics (VaR & Expected Shortfall)Intermediate

REST APIs ETL Pipelines Data Structures & Algorithms (DSA) Machine Learning Fundamentals Time-Series Regression Value at Risk (VaR) Expected Shortfall Feature Engineering

projects/

Featured work

ETL Pipeline

Real-Time Stock Market Analytics Pipeline

PythonPostgreSQL SQLAlchemyPandas yFinanceGitHub Actions

Automated ETL pipeline tracking daily price data for 2,392+ NSE-listed tickers via the yFinance API, storing historical data in PostgreSQL with automated GitHub Actions workflows.

Built an automated ETL pipeline tracking daily price data for 2,392+ NSE-listed tickers via the yFinance API
Designed and integrated a PostgreSQL database using SQLAlchemy to store and query historical stock price data
Automated scheduled data collection using GitHub Actions, removing the need for manual pipeline runs
Performed data cleaning and transformation with Pandas to prepare datasets for downstream analytics
Implemented logging and error handling to improve pipeline reliability and simplify debugging

ML & Risk Analytics

Cryptocurrency Risk Prediction & Analytics

PythonScikit-learn Binance APIPower BI Pandas

Cryptocurrency risk-analysis and time-series return forecasting pipeline using historical Binance data for BTC, ETH, SOL, XRP, and ADA with financial risk modeling (VaR/Expected Shortfall) and Power BI dashboards.

Developed a cryptocurrency risk-analysis pipeline using historical Binance data for BTC, ETH, SOL, XRP, and ADA
Engineered 30+ financial and technical features including RSI, MACD, Bollinger Bands, ATR, ADX, OBV, MFI, volatility, momentum, and lag features
Built a time-series regression model to predict next-day cryptocurrency returns using chronological train-validation-test splitting to prevent data leakage
Evaluated model performance using MAE, RMSE, and R², and performed actual-vs-predicted analysis
Implemented VaR, Parametric VaR, Expected Shortfall, coverage analysis, and strategy backtesting to assess financial risk
Developed four Power BI dashboards covering market overview, technical indicators, model performance, and risk analytics

SQL Analytics

Music Store Sales Analysis

PostgreSQLSQLPython

Analysis of the Chinook music retail dataset in PostgreSQL to answer business-driven questions on customer lifetime value, genre trends, and city-level revenue.

Analyzed the Chinook music retail dataset in PostgreSQL to answer business-driven questions on customer value, genre trends, and city-level revenue
Built advanced SQL queries using window functions and subqueries to rank customers by lifetime value and identify top-performing artists and genres by country
Designed a relational schema and imported multi-table datasets to support data-driven marketing recommendations

Full-Stack / MERN

Skill Exchange Platform

PythonJavaScript MongoDBMERN Stack WebSockets

Full-stack MERN application supporting real-time interactions using WebSockets, optimized REST APIs, and MongoDB aggregation pipelines with user engagement analytics.

Built a full-stack MERN application supporting real-time interactions using WebSockets
Designed optimized REST APIs for efficient data handling between client and server
Implemented MongoDB aggregation queries to improve query performance
Enabled user analytics and activity tracking features for platform engagement insights

Frontend

Portfolio Website

HTMLCSSJavaScript

Personal portfolio showcasing projects, skills, and professional focus — designed with a distinctive IDE-inspired layout, interactive terminal, and dynamic search.