Specializing in Power BI, Fabric, Dasboarding, ML, Deep Learning & Cloud Computing — transforming complex datasets into production-ready ML solutions.
I am a Data enthusiast and MLOps & AI Practitioner based in Germany with proven experience in data engineering, advanced machine learning, and AI deployment. I transform complex datasets into actionable insights and production-ready ML solutions.
I build scalable data pipelines, implement end-to-end ML workflows, and deploy models using Docker, CI/CD, DVC, and cloud platforms including AWS (EC2, S3, RDS, IAM), Microsoft Azure, Google Cloud Platform, and Databricks.
Pursuing a Master's degree in International Economics with a focus on Data Science at the University of Paderborn, combining strong analytical training with practical ML skills.
Advanced exploratory data analysis (EDA), KPI development, and translating data into actionable business decisions.
Hands-on experience with Microsoft Fabric including Data Factory, OneLake, Data Warehouse, and Real-Time Analytics.
Interactive dashboards, DAX, Power Query, and storytelling using Power BI.
Star schema design, dimensional modeling, and performance optimization in modern data warehouses.
EAdvanced SQL for data transformation, joins, indexing, and performance tuning across large datasets.
Using Python (pandas, NumPy, scikit-learn) for automation, analysis, and machine learning workflows.
ETL/ELT pipeline design, data integration, and transformation using Fabric Data Factory and Spark.
Working with Microsoft Azure services (Azure Synapse, Azure Data Lake) for scalable analytics solutions.
End-to-end development of predictive models including data preprocessing, feature engineering, model training, evaluation, and optimization using Python and libraries like scikit-learn.
Design and implementation of neural networks (CNNs, RNNs, Transformers) using TensorFlow and PyTorch for tasks in computer vision and natural language processing.
Dashboard analyzing video game sales trends across genres, platforms, and publishers.
Overview of Netflix content distribution by country, genre, rating, and year.
Analysis of real estate pricing and revenue trends across different property types and locations.
Dashboard analyzing video game sales trends across genres, platforms, and publishers.
Overview of Netflix content distribution by country, genre, rating, and year.
Analysis of real estate pricing and revenue trends across different property types and locations.
Analyzes user sentiments from social media comments with real-time predictions via Flask API. Built with DVC, GitHub Actions, and AWS ECR.
Predicted customer churn using Python by building a classification model analyzing customer behavior and engagement metrics.
Comparative analysis of Mercedes-Benz stock return data investigating volatility patterns across various market regimes.
ML model using Logistic Regression and Random Forest, handling imbalanced data through advanced sampling techniques.
Built a classification model enabling proactive retention strategies by identifying at-risk customers.
Let's connect and discuss how we can work together. I'm open to new opportunities.