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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Delivery-Backtest-Engine
April 25, 2026 – Present
A Python-based portfolio backtesting engine that simulates realistic rule-based portfolio rebalancing across multiple time frequencies (daily, weekly, monthly, quarterly). The system supports position-level tracking, transaction cost modeling, and cash-aware trade execution.
View ProjectCDS-Spread-Predicition-MBA-BITS
March 17, 2025 – April 30, 2025
This project aims to predict Credit Default Swap (CDS) spreads for 1-year, 2-year, and 3-year maturities using machine learning models such as Linear Regression, Random Forest, and XGBoost.
View ProjectETHUSDT-Prediction
September 22, 2023 – October 1, 2023
A repository for analysing the historical data of ETHUSDT and devising a trading algorithm around it .
View ProjectFinancial-Library
February 15, 2023 – February 16, 2023
A Financial Library for calculating various statistics, plots and much more.
View ProjectBODMAS-Cloudcraftz-Competition
January 21, 2022 – April 6, 2022
BODMAS-Cloudcraftz-Competition — GitHub repository
View ProjectGoogle-Playstore-Analytics
April 23, 2021 – April 23, 2021
A vivid data analysis of the google playstore apps dataset available on kaggle .
View ProjectEducational-Blog-Website
March 8, 2021 – September 14, 2023
An educational blog website created using Django HTML5 and CSS3 .
View ProjectML-Boston-House-Valuation-Tool
February 1, 2021 – February 1, 2021
A valuation tool that estimates the house prices in Boston .
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic in nature, focusing on data analysis, machine learning, and financial modeling. While this shows initiative, the lack of team-based projects or professional experience makes it difficult to assess cultural fit for a collaborative work environment. The project diversity aligns with a data science role, but the breadth of skills beyond core ML/Python is limited.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, and there are no completed psychometric or English tests to provide insights into communication or work attitude.