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How to Approach Machine Learning Problems
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Peter is available for hire
Hire PeterPeter Hussami
Verified Expert in Engineering
Algorithms Developer
Budapest, Hungary
Toptal member since July 3, 2017
Bio
Peter is an expert in algorithms and statistics/data science, but his specialty—which few others can deliver—is mathematical modeling. These tasks are often written out in plain language at the start, and he’s good at formalizing these problems, then providing full, working solutions and integrating them (domain expertise in audio analysis/pattern recognition, identity verification, NPL, sensor analysis, scheduling, routing, and credit scoring).
Portfolio
AB-InBev - Gen AI - India
Data Science, Machine Learning, Regression Modeling, Python, Data Analysis...
Tellimer
Machine Learning, Python, Amazon Textract, Fintech, Data Science...
Knexus Research Corporation (via Toptal)
Statistical Analysis, Python, Predictive Modeling, Git, Data Processing...
Experience
- Algorithms - 20 years
- Statistics - 16 years
- Statistical Modeling - 16 years
- Machine Learning - 15 years
- Artificial Intelligence (AI) - 15 years
- Python - 14 years
- Data Science - 12 years
- Big Data - 4 years
Work Experience
Data Scientist
2025 - PRESENT
AB-InBev - Gen AI - India
- Improved the existing shelf placement optimization algorithm with the addition of hyperparameter tuning.
- Built a full new shelf placement algorithm. The most important properties of the new program were the support of new input features and a major (30 to 1) speedup over the company's previous technology.
- Added crucial logical test checks for improved information security.
Technologies: Data Science, Machine Learning, Regression Modeling, Python, Data Analysis, A/B Testing, Git, Pandas, Testing, AI Automation, Ubuntu
Data Scientist | ML Engineer
2019 - 2022
Tellimer
- Built a proof of concept for the initial task of text extraction from PDF tables, which went so well that it earned the project a large budget.
- Created a generic text extraction algorithm based on external OCRs and custom visual processing methods.
- Built the framework for combining various outputs into higher-reliability text results.
- Added extra layers for custom, on-demand applications, notably: a highly accurate indicator processor for financial documents.
- Created a lot of infrastructure around: AWS integration, CICD, automated testing, etc.
Technologies: Machine Learning, Python, Amazon Textract, Fintech, Data Science, Financial Services, Data Modeling, Data Engineering, CI/CD Pipelines, Git, Pandas, Data Processing, Testing, AI Automation, Artificial Intelligence (AI), AI-enabled Applications, Decision Trees, Scikit-learn, K-means Clustering, Time Series Analysis, Amazon Web Services (AWS), Ubuntu, Docker
Freelance Data Scientist
2018 - 2018
Knexus Research Corporation (via Toptal)
- Investigated the possibility of replicating data by generating high-dimensional synthetic clones of the input, under strict differential privacy constraints. The solution was quite successful, the invented method might well be a mathematical novelty.
Technologies: Statistical Analysis, Python, Predictive Modeling, Git, Data Processing, Testing, AI Automation, Artificial Intelligence (AI), AI-enabled Applications, Logistic Regression, Dimensionality Reduction, K-means Clustering, Random Forests, Linear Regression, Ubuntu
Principal Data Scientist
2015 - 2018
UangTeman
- Created and maintained various statistical models for a lending company—the aim was to automate all aspects of the company's lending operations.
- Designed and implemented several successful credit risk evaluation models. Notably, I built models that supported big data, and they made inferences on heterogeneous records.
- Designed and implemented statistical identity verification tools (big data style).
- Built a plethora of scrapers for various social networks.
- Developed an OCR-based identity verification module.
- Made various further prediction models for collection, residence verification, and more.
Technologies: Linux, Amazon Web Services (AWS), Amazon, Python, Machine Learning, Data Science, Predictive Modeling, SQL, CI/CD Pipelines, Git, Data Processing, Testing, AI Automation, Artificial Intelligence (AI), AI-enabled Applications, Decision Trees, Scikit-learn, Logistic Regression, Dimensionality Reduction, K-means Clustering, Support Vector Machines (SVM), Random Forests, Linear Regression, Ubuntu, Docker
Research Contractor
2015 - 2017
Furukawa Electric
- Built a pilot system for direction detection using sound; specifically in an outdoor setting. The system's intended use is to enhance existing radar technology in the automotive field. Accuracy is lower than that of radar, but audio is a low-cost means to an orthogonal measurement.
- Developed a solution was able to measure the direction of passing cars, as well as show a consistent direction for the car it was mounted on.
- Ideated also physical solutions for alleviating wind distortion.
Technologies: Python, Audio Analysis, Predictive Modeling, Git, Testing, AI Automation, Artificial Intelligence (AI), AI-enabled Applications, Logistic Regression, K-means Clustering, Linear Regression, Time Series Analysis, Ubuntu
Researcher
2015 - 2017
General Electric
- Delivered a high-accuracy direction-detection system using sound only.
- Fused the sound and video sensor data for enhanced motion detection.
- Built a successful traffic counting and classification system that was able to count passing vehicles and separate buses, cars, and more.
- Used Python (NumPy) to build the systems.
Technologies: NumPy, Python, Audio Analysis, Git, Testing, Artificial Intelligence (AI), AI-enabled Applications, Scikit-learn, K-means Clustering, Linear Regression, Time Series Analysis, Ubuntu
Algorithm Developer
2015 - 2015
Analogy.co
- Built natural language models (NLP) for semantic data analysis.
- Developed automated semantic tagger modules for deriving meaning in the text.
- Used various algorithm optimization techniques for asymptotic speedup of the semantic search.
Technologies: Python, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Predictive Modeling, Git, Ubuntu
Algorithm Developer and Programmer
2011 - 2015
Applied Logic Laboratory
- Built a syntax parser specifically for searching through English-language patents.
- Developed an information-rich semantic representation over the parsed syntax.
- Created a search engine for matching semantic information.
- Built scrapers and built scraped data into a structured dictionary automatically.
Technologies: Java, Python, C++, C, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Git, Artificial Intelligence (AI), Ubuntu
Research Intern
2006 - 2006
SAP
- Created a server-side log analyzer. The log analyzer's purpose was to predict the identity based on user input.
- Designed the log analyzer so that it parsed server logs into structured data and estimated their distance—delivering probabilistic results.
Technologies: C++, C
Algorithm Developer and Programmer
2004 - 2005
Bioscrypt Corporation
- Participated in building the company's fingerprint recognition algorithm. The algorithmic work included image cleansing, filtering, and feature extraction.
- Wrote parts of the matching algorithm.
- Developed exported APIs to the system.
- Created test tools.
Technologies: Embedded C, C++, C
Programmer | Inventor
2000 - 2002
Connexus Corporation
- Invented one of the world's first content-based music recognition systems, it came earlier than the current market leader. The system monitored a large number of radio stations (US), to deliver high-accuracy recognition information of the contents, songs, commercials, recorded interviews etc.
- Designed the system so that it made heavy use of the Fourier transform to convert audio data into a musical score.
- Wrote fast algorithms that were supplied to match a time sequence of these fingerprints.
- Built automated management tools for recording and tagging unknown patterns; inserting them into the central database and various other smaller components.
Technologies: C++, C, Audio Analysis, Time Series Analysis
Research Intern
1998 - 1998
IBM
- Built a pilot program for converting an audio signal into musical notation. The criterion was for the musical score thus derived can be used for regenerating the original signal in a way that humans would still recognize it.
Technologies: C++, C, Audio Analysis, Time Series Analysis
Experience
Education
2005 - 2011
PhD in Mathematics
Central European University - Budapest, Hungary
1995 - 2000
Bachelor of Science Degree in Mathematics
Massachusetts Institute of Technology | MIT - Cambridge MA, USA
Skills
Libraries/APIs
Scikit-learn, NumPy, Pandas
Tools
Git, NGINX, Amazon Textract
Languages
Python, Python 3, C++, Python 2, SQL, C, Embedded C, R, Java
Paradigms
Automation, Testing
Platforms
Ubuntu, Linux, Amazon, Amazon Web Services (AWS), Docker
Storage
MySQL, PostgreSQL
Frameworks
Flask, Django
Other
Statistical Analysis, Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), Numerical Methods, Mathematics, Statistics, Algorithms, Data Science, Big Data, Data Structures, Statistical Modeling, Research, Generative Pre-trained Transformers (GPT), Predictive Modeling, Data Engineering, Data Processing, AI Automation, AI-enabled Applications, Decision Trees, Logistic Regression, K-means Clustering, Random Forests, Linear Regression, CI/CD Pipelines, Dimensionality Reduction, Support Vector Machines (SVM), Time Series Analysis, Audio Analysis, Fintech, Financial Services, Data Modeling, Regression Modeling, Data Analysis, A/B Testing
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