Peter Nemeth, Developer in Vienna, Austria
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Peter Nemeth

Verified Expert  in Engineering

Machine Learning Engineer and Developer

Location
Vienna, Austria
Toptal 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.

Portfolio

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, Computer Vision...

Experience

Availability

Part-time

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.

Work Experience

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, Sales Funnel

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
ServiceNow
  • 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 ConvertCADfiles.com, 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, 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: JavaScript, Automation, IT Service Management (ITSM), ITIL, MySQL, Reports, Dashboards, Reporting, REST APIs

APTOS 2019 Blindness Detection | Kaggle AI Competition

https://www.kaggle.com/c/aptos2019-blindness-detection
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.

Highlights:
• 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

http://numer.ai
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

https://eval.dataracing.hu/web/challenges/challenge-page/4/overview
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 (CNN), 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), GPT, Generative Pre-trained Transformers (GPT)

Frameworks

Angular, Spark

Industry Expertise

Trading Systems

2001 - 2007

Master's Degree in Computer Science

Budapest University of Technology and Economics - Budapest, Hungary

2005 - 2006

Research Year in Computer Science

Royal Institute of Technology - Stockholm, Sweden

SEPTEMBER 2022 - PRESENT

Data Analysis Using PySpark

Coursera

AUGUST 2022 - PRESENT

Natural Language Processing with Classification and Vector Spaces

Deeplearning.ai

AUGUST 2022 - PRESENT

Create a Custom Marketing Analytics Dashboard in Data Studio

Coursera

AUGUST 2022 - PRESENT

Introduction to Designing Data Lakes on AWS

Coursera

AUGUST 2022 - PRESENT

Data Analysis | Spark SQL

Coursera

AUGUST 2020 - PRESENT

Sequences, Time Series, and Prediction

Coursera

MAY 2020 - PRESENT

Fundamentals of Quantitative Modeling

Coursera

JUNE 2019 - PRESENT

Convolutional Neural Networks

Coursera

MARCH 2019 - PRESENT

Sequence Models

Coursera

FEBRUARY 2019 - PRESENT

Deep Learning Specialization

Coursera

DECEMBER 2016 - PRESENT

Professional Scrum Master

Scrum.org

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