Peter Nemeth, Machine Learning Engineer and Developer in Vienna, Austria
Peter Nemeth

Machine Learning Engineer and Developer in Vienna, Austria

Member since April 29, 2020
Peter is an experienced data scientist and a good communicator. With a background in consulting and computer science, he can quickly pick up your business requirements, translate them into technical solutions, and efficiently guide product development with data-driven insights keeping the final business solution in mind. As a solution architect, Peter has led all technical aspects of projects at top enterprises across EMEA. He also holds a master's degree in computer science.
Peter is now available for hire


  • KEG Systems LLC
    Stock Trading, Python, Data Visualization, Backtesting Trading Strategies...
  • Online Freelance Network
    Pandas, Data Visualization, SQL, Machine Learning, Predictive Modeling...
  • Freelance Work
    NumPy, Scikit-learn, OpenCV, Keras, Data Visualization, Python...



Vienna, Austria



Preferred Environment

Python, Data Analytics, Data Science, Financial Markets, Quantitative Finance, Machine Learning, Data Visualization, Data Analysis, Algorithmic Trading

The most amazing...

...project I've collaborated on was stock market forecasting that made the top 1% quants at Numerai.


  • Neural Network/Machine Learning Data Analysis

    2021 - 2022
    KEG Systems LLC
    • Developed an algorithm that predicted NHL/NBA game outcomes with accuracy that beats the bookmaker. Backtesting and live testing showed good results.
    • Developed tools to validate and accurately present the performance of a betting algorithm.
    • Implemented data pipelines to various online data sources.
    Technologies: Stock Trading, Python, Data Visualization, Backtesting Trading Strategies, Algorithmic Trading, Data Analysis, Python 3, Git, Jupyter
  • Senior Data Scientist

    2020 - 2021
    Online Freelance Network
    • Worked with product managers to support data-driven product development.
    • Answered open-ended business questions with insight based on data analytics. Analyzed customer behavior to fine-tune and improve customer experience and maximize the conversion rate.
    • Identified customer segments and created propensity models to estimate the lifetime value of these customers.
    • Performed analytics, visualization, and modeling on customer behavior and digital advertisement data. Created reports and dashboards.
    • Optimized digital advertising (Facebook ads) by estimating the value of various customer segments.
    • Developed predictive models for vetting engineers. The goal was to significantly decrease the time needed for development vetting.
    • Created ETL pipelines and did data analytics for digital marketing performance.
    • Designed the data gathering process for faster and more accurate analysis.
    Technologies: Pandas, Data Visualization, SQL, Machine Learning, Predictive Modeling, Google BigQuery, Google Data Studio, Matplotlib, Recruitment, SEO Marketing, Web Marketing, Artificial Intelligence (AI), Google Analytics, BigQuery, Statistical Data Analysis, Dashboards, B2B Lead Generation, Digital Advertising, User Behavior, Data Analysis, Jupyter
  • Computer Vision Engineer

    2019 - 2020
    Freelance Work
    • Enrolled in several computer vision competitions and developed the following computer-vision projects for them.
    • Developed a tool to detect diabetic retinopathy to stop blindness (medical image classification). It involved supervised and unsupervised ML techniques (Keras, OpenCV, Scikit-learn, NumPy, and Pandas). Top 3% result (62nd of 2986 teams).
    • Applied computer vision to detect, classify, and segment manufacturing defects in steel production, specifically on sheet steel. It involved multilabel image classification and multilabel semantic image segmentation. Top 6% result (bronze).
    • Classified and segmented cloud organizations to improve climate models for a research project for the Max Planck Institute. Top 6% result (bronze). The competition involved understanding clouds from satellite images.
    • Developed a ServiceNow app to automatically categorize and dispatch incidents. Used NLP for processing incidents written by end-users, and the app saved a significant amount of work for helpdesk agents.
    • Built an NLP app to extract key financial information from emails to automate calculations. It saves several hours of work daily for the customers and speeds up replies.
    • Developed quantitative trading algorithms to trade stock and forex markets.
    • Used a combination of classical and deep learning methods for trading. Has a strong understanding of financial markets and trading strategies.
    Technologies: NumPy, Scikit-learn, OpenCV, Keras, Data Visualization, Python, Computer Vision, Deep Learning
  • Senior Solution Architect

    2016 - 2018
    • Served as an architect for the Top 50 most strategic accounts in the EMEA (Europe, the Middle East, and Africa).
    • Supported the sales team on scoping, planning, and architecture.
    • Provided direction on keeping customer engagements aligned to ServiceNow's implementation best practices.
    • Led all technical aspects of project delivery and solution delivery.
    • Held processes workshops and gave best practices guidance.
    • Acted as a key technical focal point of the overall implementation project team.
    • Prepared all client-facing and internal deliverables that were technology-related.
    Technologies: ServiceNow, SQL, JavaScript, Angular, Web UI, Consulting, Reports, Dashboards, Reporting, User Behavior, Team Leadership, Remote Team Leadership, REST APIs
  • HP Service Manager Consultant | Web Developer (Subcontractor)

    2013 - 2016
    HP and Raiffeisen Informatik
    • Designed and built a new client service portal as a modern and more capable replacement of HP's Service Request Catalog using web services.
    • Continuously improved upon Raiffeisen's core system.
    • Introduced HP Service Manager 9.40 at Schönherr Rechtsanwälte GmbH.
    • Founded, which handles the online conversion of CAD files to commonly used exchange formats. It had 20,000 users per month and was eventually sold to a US-based company.
    Technologies: Service, IT Consulting, HP Service Manager, Reports, Dashboards, Reporting, REST APIs
  • Information Systems Architect

    2009 - 2013
    HP Austria & Switzerland
    • Designed and presented solutions to customers during workshops.
    • Implemented all modules of HP Service Manager with complex workflows.
    • Coordinated the work of others who were in geographically split-up teams.
    • Integrated HP Service Manager with external data sources, applications, and service providers using ConnectIT and SolveDirect.
    Technologies: HP Service Manager, JavaScript, Automation, IT Service Management (ITSM), ITIL, MySQL, Reports, Dashboards, Reporting, REST APIs


  • APTOS 2019 Blindness Detection | Kaggle AI Competition

    The competition focused on building a machine learning model to speed up disease detection. We worked with thousands of images collected in rural areas to help identify diabetic retinopathy automatically using deep learning.

    • It was a medical image classification task.
    • I ranked 62nd out of 2943 competing teams (top 3%).
    • I achieved a Kaggle silver medal and competitions expert status.

  • Customer Behavior Analysis

    The goal of the project was to analyze customer behavior, identify the most valuable customer segments, and design a sales funnel that is significantly more effective than the old one.

    I worked with a product manager to make data-driven decisions and optimize information gains at each step of the funnel. I also optimized ad feedback to FB to enable faster and more accurate learning.

    As a result, customer sign-ups tripled in just two months while maintaining the same level of conversion cost.

  • Test Data Analysis

    I analyzed data from multiple-choice tests to reduce testing time and improve the test-taker experience. My work included implementing a correlation analysis for test questions to avoid similar, duplicate, or erroneous questions. I also analyzed information gain per question to remove "low information" questions.

  • Quantitative Finance at Numerai

    Built quantitative models for predicting stock price movements. Made it to the top 1% of quants out of over 10,000 at Numerai—a hedge fund that crowdsources investment models. It's organized as a tournament, claiming to be "the hardest data science tournament on the planet."

  • Second Position in Dataracing Competition

    A competition organized by the National Bank of Hungary. The objective is to predict the total export production of Hungarian companies with anonymized data provided by the Hungarian National Bank. Competitors need to predict next year's export income for each company using machine learning tools based on historical data and other statistics.


  • Languages

    JavaScript, Python, SQL, Python 3
  • Libraries/APIs

    Pandas, ServiceNow REST API, REST APIs, Scikit-learn, Matplotlib, TensorFlow, Keras, NumPy, PySpark, PyTorch, OpenCV, SciPy
  • Tools

    Jupyter, BigQuery, Google Analytics, Git, TensorBoard, Spark SQL, Tableau
  • Paradigms

    Data Science, Requirements Analysis, ITIL, ETL, Behavioral Design, Automation
  • Platforms

    Jupyter Notebook, Salesforce, Google Cloud Platform (GCP), Amazon Web Services (AWS), Databricks, Docker
  • Storage

    MySQL, Google Cloud, MongoDB, NoSQL, Data Lakes
  • Other

    Reports, Data Reporting, Image Recognition, Deep Neural Networks, Algorithms, Analytics, Machine Learning, Computer Vision, Artificial Intelligence (AI), Consulting, Data Analytics, Data Analysis, Exploratory Data Analysis, ServiceNow, Communication, IT Consulting, IT Service Management (ITSM), Team Leadership, Remote Team Leadership, Image Processing, Predictive Analytics, Big Data, Predictive Modeling, Time Series Analysis, Regression Modeling, Google BigQuery, Google Data Studio, Statistics, Financial Data Analytics, Trading, Data Mining, Statistical Modeling, Dashboards, Analytical Dashboards, Financial Analysis, Deep Learning, Convolutional Neural Networks, Reporting, Object Recognition, Object Detection, Image Classification, Classification Algorithms, Data Visualization, Backtesting Trading Strategies, Algorithmic Trading, User Behavior, Decision Trees, Neural Networks, Random Forest Regression, Time Series, Development, Data Modeling, Financial Markets, Statistical Data Analysis, Advertising, Paid Advertising, eCommerce, B2B Lead Generation, Digital Advertising, Service, Google Tag Manager, Web Scraping, Quantitative Modeling, Quantitative Finance, Sales Funnel, Recruitment, SEO Marketing, Web Marketing, Web UI, Stock Trading, Data Engineering, Natural Language Processing (NLP)
  • Frameworks

    Angular, Spark
  • Industry Expertise

    Trading Systems


  • Master's Degree in Computer Science
    2001 - 2007
    Budapest University of Technology and Economics - Budapest, Hungary
  • Research Year in Computer Science
    2005 - 2006
    Royal Institute of Technology - Stockholm, Sweden


  • Data Analysis Using PySpark
  • Natural Language Processing with Classification and Vector Spaces
  • Create a Custom Marketing Analytics Dashboard in Data Studio
  • Introduction to Designing Data Lakes on AWS
  • Data Analysis | Spark SQL
  • Sequences, Time Series, and Prediction
  • Fundamentals of Quantitative Modeling
    MAY 2020 - PRESENT
  • Convolutional Neural Networks
    JUNE 2019 - PRESENT
  • Sequence Models
    MARCH 2019 - PRESENT
  • Deep Learning Specialization
  • Professional Scrum Master

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