Software Developer | Algo-Backtesting Specialist | R&D of Trading Algorithms | Learning Quants
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Assessing your cultural and operational fit
CppPractice-LowLatency
March 16, 2026 – Present
Low latency memory based or memory managed C++ practice
View ProjectNormal_Distribution
February 15, 2025 – February 17, 2025
Explaination of Normal Distribution and its application in financial markets.
View ProjectTrendFollowing_Model
February 12, 2025 – February 12, 2025
Document on Trend Following strategy backtesting.
View ProjectSpread_Analysis-and-Mean_Reversion_Technique
January 15, 2025 – January 29, 2025
To find and analyze the mean reversion pair trading strategy
View ProjectBacktesting_Ratios
January 10, 2025 – January 10, 2025
Explaining and listing down some essential backtestin ratios to calculate and analyze.
View ProjectCointegration_Test
January 7, 2025 – January 10, 2025
Study about the co-integration test, to find pairs that are co-integrated.
View ProjectStationarity_and_ADF_test
January 6, 2025 – January 7, 2025
Explains about Stationarity, and the ADF test
View ProjectStock_vs_Benchmark_performance
January 5, 2025 – February 5, 2025
Comparison of cumulative returns of a stock vs the index performance
View ProjectCAPM_Model
December 30, 2024 – January 5, 2025
Short analysis on Expected returns using the CAPM formula, for all Nifty50 stocks.
View ProjectAnalysis_of_Indian_Indices
October 9, 2023 – May 4, 2024
Explore historical performance and analysis of Indian stock market indices. Dive into data-driven insights, code, and visualizations for Nifty 50, Bank Nifty, sectoral indices, and more. Discover trends, volatility, and statistical measures.
View ProjectCultural Fit Analysis
The candidate's projects are exclusively personal and heavily focused on quantitative finance, specifically algorithmic trading and market analysis. While this shows initiative, the lack of diversity in project types (e.g., machine learning applications beyond finance, data engineering, MLOps) and the absence of team-based projects suggest a potentially narrow scope of experience for a general Data Scientist role. The experience level is 0, indicating a junior profile, which might not align with senior-level expectations for cultural fit in terms of broader team contributions or mentorship.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's projects are all personal and lack team collaboration context. No psychometric test results are available.