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

Virtusa

Machine Vision Data Operations Specialist 

The Home Depot

I lead the development and optimization of end-to-end data pipelines for Generative AI, with a strong emphasis on scalability, performance, and observability. Leveraging Google Cloud Platform and Apache Airflow, I automate and orchestrate complex workflows, ensuring seamless infrastructure provisioning through infrastructure-as-code principles. I play a key role in designing and implementing CI/CD pipelines that drive operational efficiency and system reliability. Additionally, I collaborated on the development of an proprietary tool for versioning and managing AI prompts, significantly streamlining model administration processes. My work extends to leveraging Dataflow for high-performance data processing and collaborating with a dedicated computer vision team, enhancing the AI ecosystem across diverse projects.

MLOps Engineer

Auto Avaliar

As the technical lead for the data side of Car Invest, I specialized in building data pipelines, deploying AI models, and developing backend systems on Google Cloud Platform. Working across both backend and data departments, I managed ETL processes for this platform, which supports data-driven decision-making for car dealerships. My expertise includes:

- AI model deployment and development
- Scalable data pipelines and data product APIs

Passionate about data, machine learning, and artificial intelligence, I have a strong background in backend, data science and data engineering. I specialize in developing APIs, implementing and deploying ML models, and building scalable data pipelines and ETLs on Google Cloud Platform (GCP) and Azure, ensuring compliance with LGPD.

Currently based in São Paulo, Brazil, I work with large language models (LLMs) and big data architectures, leveraging cutting-edge AI techniques to process and analyze large-scale datasets efficiently. My expertise spans machine learning engineering, MLOps, backend development, and big data processing, integrating high-performance solutions into production environments.

Additionally, I have experience with Infrastructure as Code (IaC), automating cloud infrastructure deployment to ensure scalability, security, and efficiency in machine learning and data engineering workflows.

Technical Expertise
✔ Programming & Data Science: Python (Pandas, NumPy, TensorFlow, Scikit-learn), R (dplyr), SQL
✔ Big Data & Data Engineering: Scalable ETLs, distributed processing, data pipelines, API development
✔ MLOps & DevOps: Docker, Docker Compose, Linux Bash, Github Actions
✔ Cloud & AI Services: GCP (Vertex AI, BigQuery, Cloud Run, Datastore, Google Storage)
✔ Infrastructure as Code (IaC): Terraform, Ansible

taplio

The Battle

Banias Baabe

Antonio Mario Pio Cardoso Soares Frioli

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