MHP – A Porsche Company

- Developing multimodal Retrieval Augmented Generation applications on company data with Large Language Models
- Building an LLM-based Quality Evaluator and ML-based Duplicate Detection Method for Software Bug Tickets

Data Scientist

Bosch Power Tools

- Implementation and evaluation of probabilistic deep learning models for demand forecasting on AWS SageMaker

Master Student Data Science

- Development of a tool for automated data analysis and visualization in SAP Analytics Cloud
- Implementation of time series forecasting and outlier detection models

Working Student Data Science

Mercedes-Benz AG

- Speeding up the assembly process by using machine learning to predict throughput times and errors on Azure Databricks
- Automation of graph visualization for the optimization of assembly analysis

Fraunhofer IPA

- Implementation and evaluation of a generative deep learning model for image data augmentation for cutting edge patterns
- Implementation of scientific papers in Python

Bachelor Student Deep Learning

MAHLE

- Analysis of engine data and application of machine learning for prediction in piston temperature measurement

Intern Data Analysis & IT Project Management

I make learning Data Science effortless for you | Data Science @ Bosch

Hi 👋🏻
I'm Banias, Data Scientist at MHP.

Applying new technologies and methods in Data Science is my passion.

Through my experience and continual learning, I've gained valuable insights and tips that I love sharing with Data Scientists, Machine Learning Engineers and builders like you.

If you're looking for practical advice, helpful resources, and articles on the latest trends or best practices in the field, you're in the right place.

Let's connect and stay updated on the exciting world of Data Science together. Feel free to reach out, read my articles, and let's grow our knowledge and network. :)


Note: My views are my own and don‘t represent my employer.

Banias Baabe

opennudge

- driving not-for-profit organization building open-source software
- creating developer-first tooling amplifying software creation
- spreading new best practices and paradigms in software development
- bridging disciplines across automation, AI/DL/LLM and DevSecOps

Developer and founder

InovIntell

- established the AI-health science company with internal stakeholders
- directed and mentored technical and research teams (10 people)
- defined and created a robust technical culture, practices, pipelines
- programmed in LLM, backend, data science, DevOps and cloud areas

Chief Technology Officer

WinCan

- co-developed technical and scientific plan for company's AI offering
- guided the development of the computer vision algorithms
- reviewed code quality and PRs, mentored ML team
- mentored and provided strategic advice to the machine learning team

Deep learning advisor

Moises

- optimized audio neural networks for mobile devices deployment
- advised on torchscript/CoreML conversion to accelerate inference

AiCore

- designed and created Python, Linux, ML, DL, and Ops course units
- taught numpy, PyTorch, sklearn, Docker, Kubernetes, Kubeflow (among others)
- consecutively chosen as company's best instructor by the students
- conducted mock interviews, coached and mentored over 100 students

Head of content & instructor

Artplanet

- engineered a low-maintenance, cost-efficient neural network art tagger
- created C++ optimized AWS Lambda inference engine for neural networks
- handled full SDLC, including data science, ML, and AWS deployment

Machine Learning Engineer

Codete

- built and validated dockerized Keras ↔ TensorFlow neural network converter (ONNX-like)
- researched AI use cases (e.g. NLP, R to Python ML algorithms conversion)
- co-authored commercial machine learning courses (NLP, CV, tabular data)

Internal ML Researcher

Passionate about computer science and AI, with focus on code design and architecture. People-oriented leader promoting open source, interested in the intersection of technology and other fields.

taplio

The Battle

Banias Baabe

Szymon Maszke

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