Kázmér Nagy-Betegh

Kázmér Nagy-Betegh



Purpose of The Website

I use this site to give you a quick overview of myself and some highlights from my project and work experiences.

Download my resumé.


I am from Cluj-Napoca Romania, born in a Hungarian family, I finished high school there.


Moved to London for University, where I studied Electrical and Electronic Engineering at UCL with an emphasis on Internet of Things and Machine Learning. I graduated with First Class Honours and my Masters project focused on power efficient indoor localisation using Ultra-Wideband won best project within the department. It was published in 2021 as part of the ICL-GNSS 2021 conference.

After working as a Software Engineer for a year at Bosch I’ve returned to school to complete a masters in Management and Analytics at London Business School.

A brief overview of my work experience:

I have worked a month in San Sebastian, Spain at Elektra, an international Electrical solutions distribution and Automation company, where I researched industry 4.0 technologies which cover internet of things, machine learning and robotics. I have worked as Business Analyst at Humatica during the summer of 2019, working on growth strategies for a client in wealth management, in this role I performed research and financial modeling. Starting 2020 November I worked at Bosch Budapest, as a software engineer as part of the near range camera visualisation team developing solutions in C++ and Python.

Since 2022 November I have been working at Flexciton London. Flexciton is focused on delivering advanced scheduling solutions for semiconductor fabs. I work as a Customer Solutions Engineer.


I have played water polo at national level for 10 years in Romania and 4 years at University at BUCS level.

My hobbies include: skiing, culinary experiences, diving, hiking, movies

Some of my favourite books:

  • The Last Samurai by Helen Dewitt
  • The Sun Also Rises by Ernest Hemingway
  • Flowers for Algernon by Daniel Keyes
  • Do androids dream of electric sheep? by Philip K. Dick
  • Artificial Intelligence
  • Internet of Things
  • Information Retrieval
  • Business Strategy
  • MSc Masters in Analytics and Management, 2022

    London Business School

  • MEng Electrical and Electronic Engineering, 2020

    University College London



Stats and Visualisation


ML, Visualisation, General

Business Analytics


Customers Solutions Engineer
Nov 2022 – Present London

Responsibilities included:

  • Working with customers to understand their needs and requirements
  • Designing and implementing solutions to meet customer needs
  • Working with the development team to implement new features
  • Working with the sales team to create proposals and presentations
Bosch GMBH
Software Engineer
Bosch GMBH
Dec 2020 – Jul 2021 Budapest

Responsibilities included:

  • Implementing new features in C++ for the Parking Video Visualisation
  • Code improvements and debugging
  • Development Process Improvement
Digitalisation Consultant
Sep 2020 – Dec 2020 Cluj-Napoca, Romania

Responsabilities included:

  • Developed a Micrososft Power Automate based tool for the company to track Product Returns
  • Helped in definining the new fully digital process and the information flow between teams.
Business Analyst Intern
Jun 2019 – Aug 2019 London

Responsibilities included:

  • Modelled the size of the High Net-Worth wealth management market and segmented it into 20 dimensions for the client.
  • Wrote a 5 and 10 year outlook report on the effects of Automation and AI on operating models across industries, providing a roadmap for sectors where management consulting might be needed.
  • Presented the analyses techniques and data sources in the excel models, during 3 client meetings accompanying the partner and manager
Industry 4.0 Research Intern
Elektra S.A.
Aug 2017 – Sep 2017 San Sebastian, Spain

Responsabilities included:

  • Researched topics that fall under the umbrella term Industry 4.0, such as: predictive maintenance, AR assisted production lines, machine learning, collaborative robots.
  • Wrote, recoded and edited one in-depth explanatory and one marketing video about the technologies enabling the next industrial revolution, both of are still in use at the company.
  • Shadowed the head of the innovation lab at the company, to learn about their digitalisation efforts.


Tableau London House Prices

Tableau London House Prices

Data Story that explores the London house price evolution.

Tableau Covid Dashboard

Tableau Covid Dashboard

Covid Tableau data dashboard relying data as of Nov 14, 2021

Bike Rental Data London

Bike Rental Data London

Some visualisation around London Bike Rentals; Page Still under construction, Futher insights and examplanations will be added

Linear Regression to Predict Interest Rate

This is a short intro to linear regression with exampls inspired by my Data Science for Business class at LBS.

Metropolitan Police Stop and Search Data

Metropolitan Police Stop and Search Data

Here are some results from my workings with the the London metropolitan police data for a LBS school assignment and the visualisations I have come up with.

Apple Stock Price Deep Learning

Apple Stock Price Deep Learning

Evaluating the performance of LSTM, RNN and CNN on predicting apple Stock Price based on historical price and volume data.

London House Prices

London House Prices

London House Price prediction using statistical machine learning techniques

Tidytuesday Astronauts Dataset Dashboard

Tidytuesday Astronauts Dataset Dashboard

Dashboard with insights from the Astronut dataset from Tidy Tuesday Challange

Face Categorisation using Python

This is an overview of one of my machine learning assignments that I have completed at UCL

2020 US Election Results vs Vaccination

2020 US Election Results vs Vaccination

Introduction The purpose of this exercise is to reproduce a plot using your dplyr and ggplot2 skills. Read the article The Racial Factor: There’s 77 Counties Which Are Deep Blue But Also Low-Vaxx.

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