
ML @ Finance
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Applying modern AI technologies to automate document processing.
ETH Zürich
M.Sc., Computer Science with focus in Visual Computing
January 1, 2009 – January 1, 2011
Sofia University St. Kliment Ohridski
B.S., Computer Science
January 1, 2005 – January 1, 2009
Sofiiska Matematicheska Gimnazia
High School Diploma, Mathematics and English
January 1, 1997 – January 1, 2005
Hedge Fund
Senior Software Engineer
June 1, 2020 – Present
Irvine, California, United States
HyperScience
Director of Engineering (Machine Learning)
April 1, 2019 – March 1, 2020
HyperScience
Head of Machine Learning
January 1, 2017 – April 1, 2019
HyperScience
Machine Learning Engineer
January 1, 2015 – January 1, 2017
SoundCloud
Backend Engineer
November 1, 2012 – August 1, 2014
Sofia, Bulgaria
Software Engineer
October 1, 2011 – November 1, 2012
Zurich
NVIDIA
Software Intern
June 1, 2008 – August 1, 2008
San Francisco Bay Area
MM Solutions
Software Engineer
January 1, 2006 – January 1, 2009
Sofia, Bulgaria
Image compression algorithm:
January 1, 2011 – Present
An image compression algorithm that uses PCA transform to find an image-optimized color space that allows sparse representations in over-complete DCT dictionary. The project was implemented first in Matlab. Later we created a high-performance CUDA implementation.
Iterative Methods for Matrix Factorization with Missing Data (master thesis)
January 1, 2011 – Present
I compared different methods for factorization of large sparsely observed matrices, developed algorithm improvements that significantly reduce the computational complexity of the best method and suggested a prior that improves the results when applied to affine structure-from-motion problems.
Depth from focus/defocus application for N900 phone
January 1, 2010 – Present
An application that extracts depth information from a series of pictures of single scene taken with varying focus distance. The application was implemented on a N900 phone using C++ and QT libraries.
XCS236 - Deep Generative Models
Stanford Online
June 24, 2026 – Present
Functional Programming Principles in Scala
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning research-oriented projects (ETH Zürich thesis), large tech companies (Google, SoundCloud), and startups (HyperScience). The progression into leadership roles in Machine Learning aligns with a growth-oriented culture. However, the target role of 'Data Analyst' seems to be a significant shift from their senior/director-level Machine Learning and Software Engineering roles, which might indicate a mismatch in career trajectory or expectations for the specific role. The projects are highly technical and research-heavy, indicating a strong inclination towards complex problem-solving. The lack of explicit 'Data Analyst' specific projects or experience in the provided data makes it difficult to fully assess cultural fit for that specific role.
Soft Skills & Operational Fit
The candidate's career progression from Engineer to Director of Engineering (Machine Learning) suggests strong leadership, problem-solving, and project management skills. The descriptions of designing and implementing distributed systems indicate a collaborative and strategic approach to complex technical challenges. However, without specific psychometric test results or interview data, a detailed assessment of soft skills and operational fit is limited.