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# John Doe |
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π Berlin, Germany |
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π§ [email protected] |
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π +49 123 456789 |
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π [LinkedIn](https://linkedin.com/in/johndoe) β’ [GitHub](https://github.com/johndoe5629) |
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## π§ About Me |
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Experienced software engineer with 10+ years in full-stack development, including backend architecture and modern frontend frameworks. Known for my problem-solving mindset and adaptability across tech stacks. Recently, I have developed a strong interest in **data science and machine learning**, driven by my passion for data-driven decision-making and advanced analytics. Iβm actively seeking opportunities to leverage my engineering background in the field of data science. |
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## π Education |
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**M.Sc. in Computer Science** |
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*Technical University of Munich (TUM)* β Munich, Germany |
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_2011 β 2013_ |
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**B.Sc. in Computer Science** |
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*University of Stuttgart* β Stuttgart, Germany |
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_2008 β 2011_ |
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**Professional Development Courses** |
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- *IBM Data Science Professional Certificate*, Coursera (2024) |
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- *Deep Learning Specialization*, deeplearning.ai (2024) |
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- *DataCamp Tracks*: Python for Data Science, Data Analyst in Python |
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## πΌ Work Experience |
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### **Senior Frontend Developer** |
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**TechWorks GmbH** β Berlin, Germany |
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*2020 β Present* |
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- Led a team of 4 frontend developers in designing SPAs using React and TypeScript |
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- Collaborated with data analysts to design dashboards and data visualizations |
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- Integrated REST APIs and GraphQL for scalable frontend architecture |
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### **Full-Stack Developer** |
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**NextGen Solutions** β Hamburg, Germany |
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*2016 β 2020* |
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- Designed and maintained microservice-based architecture with Node.js and Express |
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- Developed internal analytics tools in Python and Flask |
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- Contributed to DevOps initiatives: Docker, CI/CD, AWS Lambda functions |
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### **Backend Developer** |
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**ByteForge AG** β Stuttgart, Germany |
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*2013 β 2016* |
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- Developed and optimized backend systems using Java and PostgreSQL |
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- Worked on authentication and authorization systems for enterprise clients |
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- Refactored legacy codebase improving API performance by 30% |
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## π Data Science Projects |
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- **Customer Churn Prediction** |
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Logistic regression model trained on real-world telecom dataset; achieved 85% accuracy. Deployed using Flask and Docker. |
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- **Movie Recommender System** |
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Collaborative filtering project using Python, Pandas, and Surprise library. |
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- **EDA on COVID-19 Global Data** |
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Performed extensive exploratory data analysis and visualized trends using Seaborn and Plotly. |
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## π§° Technical Skills |
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**Languages:** Python, JavaScript (ES6+), Java, SQL, TypeScript |
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**Frameworks:** React, Node.js, Flask, Express |
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**Tools & Libraries:** Pandas, NumPy, scikit-learn, TensorFlow, Keras, Matplotlib, Plotly |
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**Databases:** PostgreSQL, MongoDB, Redis |
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**Cloud & DevOps:** AWS (EC2, S3, Lambda), Docker, GitHub Actions |
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**Others:** REST APIs, GraphQL, CI/CD, Agile (Scrum), JIRA |
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## π Languages |
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- **English:** Full professional proficiency |
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- **German:** Native |
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- **Spanish:** Intermediate |
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## π Certifications |
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- IBM Data Science Professional Certificate (2024) |
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- AWS Certified Developer β Associate (2023) |
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- Deep Learning Specialization β Andrew Ng (2024) |
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## π€ References |
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Available upon request. |