Akanksha Thakur

Akanksha Thakur

Attended CCS (Chaudhary Charan Singh)University

Delhi, IndiaData Science and Analytics
2roles
28skills
4education
4credentials

About

MCA student with internship experience in data science and projects in data analysis, machine learning, fraud detection, and disaster management systems.

Experience

Software Engineer Intern

HashedBit Innovations

3 mos · Gurugram, Haryana, India

I have completed pioneer projects.

Data Science Intern

HashedBit Innovations

May 2024 – July 2024

Built a content-based recommendation engine processing 1,000+ products across 10+ grocery categories using Python, Pandas, and Scikit-learn cosine similarity. Developed Frequently Bought Together logic achieving a 15% click-through rate in an A/B test, designed to increase average order value by 10%.

Education

Jaypee Institute Of Information Technology

Master of Computer Applications - MCA

Aug 2025 - May 2027

CCS (Chaudhary Charan Singh)University

Bca, Bca

2022

Jaypee Institute Of Information Technology

MCA

2027

CGPA: 7.5

Greater Noida Institute of Technology

BCA

2025

CGPA: 7.88

Skills

CPythonJavaSQLHTMLCSSJavaScriptMySQLMachine Learning AlgorithmsData AnalysisData PreprocessingData CleaningData VisualizationAdvanced ExcelTableauPower BIGitGitHubVS CodeData StructuresComputer Science FundamentalsPandasScikit-learnXGBoostFlaskDAXBorutaDijkstra’s Algorithm

Projects

Banking Dashboard – End-to-End Data Analysis using Power BI

Built an interactive multi-page Banking Dashboard with Home, Loan, Deposit, and Summary pages. Performed data cleaning, transformation, exploratory data analysis, and managed a 24-column dataset in MySQL. Standardized categorical variables and created Income Band categories in Power BI.

Transaction Fraud Detection - End-to-End ML Pipeline

Developed a fraud detection machine learning model, performed feature engineering and exploratory data analysis on highly imbalanced data, used Boruta for feature selection, and compared seven models. Selected XGBoost with 94.4% precision and 82.9% recall and deployed it as a Flask API.

Smart Disaster Management - Real-time Response Dashboard

Developed a real-time dashboard for active incidents including fires and floods, with auto-dispatch of emergency resources. Used Dijkstra’s algorithm for shortest-route computation, built a disaster and resource-state simulation engine, and added dynamic incident priority escalation.