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PontusHovb/README.md

Hi there 👋

My name is Pontus and I'm a 1st year MSc-student in Financial Mathematics at KTH - Royal Institute of Technology with previous exchange studies at National University of Singapore (NUS) and a completed BSc in Industrial Engineering & Management from KTH. Selected coursework include Portfolio Theory & Risk Management, Quantitative Finance, Machine Learning, Language Engineering, Probability Theory, Calculus, Applied Computer Science, Regression Analysis, Game Theory and Markov Processes.

Previous professional experience includes Visiting Associate @ BCG Platinion (tech/IT-strategy consulting internship), Junior Quantitative Analyst @ Söderberg & Partners building and maintaining quantitative models for money market, fixed income and equity funds using Python (pandas, numpy, scikit-learn), SQL and VBA. I've also worked as Intern/business developer @ If P&C Insurance in commerical pricing where I analyzed claims data to assess, model and price commerical property risk using SQL & SAS as well as building dashboards for portfolio follow-up in PowerBI using DAX and PowerQuery.

Programming experience in Python, SQL, VBA and R with some experience in MATLAB, JavaScript and C/C++.

Projects 🚀

Sudoku Solver 🧩

Backtracking Average time per sudoku Crook's Algorithm
In this project I have implemented different algorithms (bruteforce, backtracking, candidate checking, placefinding and Crook's algorithm) for solving sudokus to test both their speed, accuracy and solving ability. This is done both in Python and C to build the most efficient and quickest algorithms. While bruteforce and backtracking algorithms are fast and reliable to solve all sudokus, they have lower accuracy (a lot of wrong tries before reaching the correct solution). Instead, more human-like algorithms such as the pen-and-paper based Crook's Algorithm can perform on similar level in terms of speed and solving ability but with perfect accuracy (only inputting a number if it is correct).

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