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baris2828/README.md

Hi, I'm Baris 👋

Data Scientist & ML Engineer building tools at the intersection of machine learning, cloud infrastructure, and interactive data visualization.

About Me

I work across the full data lifecycle — from raw data engineering and model building to production APIs and decision-ready dashboards. What sets my profile apart is the combination of a modern data-science stack with a strong engineering foundation: I'm equally comfortable with low-level and scientific computing (C, Fortran), enterprise systems (SAP S/4HANA, Oracle), and cloud-native ML services on GCP.

This breadth lets me bridge classical engineering rigor with state-of-the-art machine learning — turning data into reliable, deployable, and well-visualized products.

Tech Stack & Skills

Programming Languages

Python SQL Java Fortran C HTML

Machine Learning & AI

Scikit-Learn TensorFlow Deep Learning NLP Generative AI RAG Prompt Engineering Supervised & Unsupervised Learning Recommendation Systems

Cloud, Data Engineering & DevOps

GCP BigQuery Docker Azure DevOps UNIX/Linux FastAPI ETL Pipelines APIs & Web Scraping

GCP focus: Cloud Functions, Cloud SQL

Data Visualization & Web Apps

Power BI Tableau Streamlit Gradio Looker Studio

Databases & Data Analysis

pandas Seaborn MySQL Oracle SAP S/4HANA

Process Automation & Agile

n8n BPMN Requirements Engineering SCRUM/SAFe Jira Confluence

Featured Projects

A selection of work spanning machine learning, cloud services, and data visualization.

Machine Learning & Data Science

Project Description Stack
ConsultIQ Business-development cockpit for German IT consultancies — unsupervised ML builds ICPs & prioritises B2B leads · ▶ Live Demo Streamlit, scikit-learn, Plotly, Pydeck
K-Means 3D Visualizer Interactive 2D/3D clustering explorer with CSV upload, Elbow method & Silhouette scoring Streamlit, Plotly, Scikit-Learn
CLT Real-World Analysis Central Limit Theorem simulation on e-commerce transaction data with 2x2 statistical dashboard NumPy, SciPy, Seaborn
Haemorasis Reliability Eval Evaluation framework for AI blood-cell analysis — Wilson CIs & Monte Carlo benchmarks at n=10,000 vs n=100 SciPy, Matplotlib, Pillow
Eniac A/B Test Optimization Four-arm A/B test analysis with Chi-Square, Bonferroni correction & relative-lift framing pandas, SciPy, Matplotlib

Engineering & Dashboards

Project Description Stack
Green-AI API REST API to estimate, compare & optimize cloud workload carbon footprints across AWS, GCP & Azure FastAPI, Docker, Cloud Run
Predictive Maintenance Dashboard 87,600-row sensor simulation for a German factory with Power BI Key Influencers analysis Python, Power BI, DAX

LinkedIn Email GitHub

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  1. ConsultIQ ConsultIQ Public

    ICP segmentation & lead prioritisation for German IT consultancies — K-Means/DBSCAN + PCA scoring, Streamlit live demo

  2. kmeans-3d-visualizer kmeans-3d-visualizer Public

    Interactive 3D K-Means Clustering Explorer with Streamlit, Plotly, and Scikit-Learn

    Python 1

  3. eniac-ab-test-optimization eniac-ab-test-optimization Public

    Four-arm A/B test analysis (Chi-Square + Bonferroni) for an e-commerce homepage CTA — Python, scipy, pandas

    Jupyter Notebook

  4. green-ai-api green-ai-api Public

    Estimate, compare, and optimize the carbon footprint of cloud AI workloads

    Python

  5. haemorasis-benchmark-framework haemorasis-benchmark-framework Public

    Statistical reliability evaluation of an AI blood-cell pipeline — Wilson CIs & Monte Carlo quantify the 10,000-cell vs 100-cell precision gap

    Python

  6. predictive-maintenance-dashboard predictive-maintenance-dashboard Public

    Predictive-maintenance case study — simulated factory sensor data (Python) + Power BI dashboard with Key Influencers root-cause analysis

    Python