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01/2023 - 03/2023
Freelance Senior Data Scientist & Full Stack Developer
Digital Equity Analytics GmbH. Remote

Senior Data Scientist & Full Stack Developer

End-to-End Machine Learning System Development Led a complex data engineering project, delivering a comprehensive machine learning solution from conception to deployment with strict security and performance requirements. Technical Achievements Machine Learning & Data Engineering Development of a machine learning solution with complex algorithms and statistical modeling Implementation of data analysis, data engineering, and visualization solutions Built an end-to-end machine learning system with production-grade architecture Set up PostgreSQL database architecture with optimized schema and multiple replicas Technology Stack & Infrastructure Python Ecosystem: scikit-learn, TensorFlow, pandas, polars, and Dash AWS Services: Lambda, Athena, EC2, SageMaker, ECS, EKS, ElastiCache DevOps: GitHub Actions for CI/CD and test automation Database: AWS RDS PostgreSQL with multiple replicas and analytics dashboard Monitoring: Comprehensive logging and performance monitoring Project Management & Delivery Taking on project responsibility for complex and sensitive data requirements Prioritization of tasks and on-time delivery of data infrastructure Implementation of GDPR-compliant data processing workflows Close collaboration with stakeholders to ensure business requirements were met This project demonstrated my ability to architect complete machine learning solutions while maintaining high standards for data security and system reliability of data security and system reliability.
01/2022 - 08/2022
Guest Lecturer for Machine Learning: Healthcare Data Analytics
University of Applied Sciences, Kempten. Kempten, Germany

Guest Lecturer for Machine Learning

Academic Teaching & Knowledge Transfer Developed and delivered a comprehensive machine learning curriculum focused on healthcare applications, transferring industry expertise to students. Academic Contributions Curriculum Development Teaching data transformation principles and the data value chain Fundamentals of machine learning, including Random Forest and Support Vector Machines Introduction to Neural Networks and Deep Learning architectures Convolutional Neural Networks and Recurrent Neural Networks for image processing and sequence analysis Advanced Topics & Practical Applications Big Data concepts: MapReduce paradigm and Data Warehouse architectures Practical applications with visualization and prototyping in Jupyter Notebooks Real-world case studies from healthcare data analytics Integration of theoretical concepts with practical implementation Ethics & Professional Standards Ethical aspects and data protection in the application of AI in healthcare GDPR compliance in data science projects Responsible AI development and deployment practices Industry best practices for healthcare data handling Professional Recognition Academic Opportunity Received an offer for Full Professorship (W2) in Data Science in Healthcare Opportunity declined to pursue industry leadership roles Recognition of expertise in both academic and practical applications This teaching experience allowed me to formalize my knowledge while contributing to the academic community and preparing students for careers in data science and healthcare technology.
01/2021 - 06/2022
Vice President Engineering / Distinguished Engineer
Smart Reporting GmbH. Munich, Germany

Vice President Engineering

Engineering Leadership in Healthcare Technology Advanced to VP Engineering to lead the development organization. Successfully managed a 35-person engineering team while driving architectural transformation in healthcare AI. Leadership & Organizational Impact Team Leadership at Scale Professional and disciplinary management of the Development Department with 35 FTEs Budgeting, recruiting, and comprehensive team organization Agile transformation of software development processes across multiple teams Implementation of career development programs and technical mentorship Strategic Technical Leadership Migration from monolith to microservices architecture (Java / TypeScript) Designed data flow and integration strategies for healthcare data sources Overall responsibility for development projects and data architecture Roadmap creation and OKR definition for product development Innovation & Technical Excellence Healthcare AI & Data Systems Development of ontology-based medical graph database (TUM Data Innovation Lab collaboration) Implementation of cloud services (Docker and Kubernetes on AWS and On-Premise) Certified development processes according to ISO 13485 medical device standards Advanced data processing pipelines for medical imaging and structured reporting Industry Partnerships & Compliance Technical partner management with Siemens Healthineers and GE Healthcare Ensuring GDPR compliance and medical data protection standards Leading cross-functional initiatives with regulatory and clinical teams This role combined significant management responsibility with technical leadership in healthcare technology.
12/2019 - 01/2021
Principal / Senior Software Engineer
Smart Reporting GmbH. Munich, Germany

Principal Software Engineer

Healthcare AI Development & Technical Leadership Progressed through multiple technical roles while leading complex AI projects in healthcare, demonstrating strong technical capabilities and growing leadership responsibilities. AI & Machine Learning Innovation Healthcare AI Development Development of software for structured reporting in radiology and pathology Implementation of AI-optimized data workflows to increase efficiency of medical activities Leadership of the KI-Beta project: AI-based analysis of clinical images on prostate datasets ImageREPORT: Advanced system for automated analysis of medical images and structured reporting Research & Development Partnerships Responsible for TUM Data Innovation Lab: Cooperation project to build an ontology-based medical graph database Collaboration with AWS on automated diagnosis and reporting of Covid-19 patients PlanQK project: Platform for quantum computing in artificial intelligence Support in technical partner management with Siemens Healthineers and GE Healthcare Technical Expertise & Implementation Full-Stack Development & Infrastructure Quantum computing, machine learning, data science, and web development Programming in TensorFlow, React, TypeScript, JavaScript, WebAssembly, Python Advanced data processing with NumPy, SciPy, Pandas, and scikit-learn Cloud-native architecture design and implementation Innovation Impact Bridged academic research with practical healthcare applications Contributed to medical device software under strict regulatory requirements Worked on integrating quantum computing concepts in healthcare AI This role marked the transition from individual contributor to technical leader, applying deep AI/ML expertise to healthcare challenges.
08/2019 - 12/2019
Freelance Senior Software Engineer
Horváth & Partner GmbH. Stuttgart, Germany

Senior Software Engineer - Horváth & Partner

Data Analytics & Optimization Solutions Contributed to the Steering Lab (Data Science Department) at a management consulting firm, developing analytics applications for strategic business optimization. Technical Development & Innovation Advanced Analytics Platform Development of data analysis application for optimization and visualization Application for combinatorial optimization and data visualization Data processing pipeline using Flask, pandas, NumPy, and SQL Creation of interactive dashboards for complex business metrics Technology Stack & Architecture Backend: Flask framework for robust API development Data Processing: pandas, NumPy for high-performance data manipulation Database: SQL optimization for large-scale data queries Frontend: Angular for responsive user interfaces Deployment: Docker containerization for consistent deployment across environments Knowledge Transfer & Collaboration Technical Leadership & Mentoring Guidance for software developers on advanced data processing techniques Knowledge transfer of best practices in data pipeline architecture Collaboration with consulting teams to translate business requirements into technical solutions Documentation and training materials for internal development teams Business Impact Enabled consultants to process and analyze large datasets more efficiently Reduced time-to-insight for client engagements through automated analytics Improved data visualization capabilities for client presentations Contributed to the firm’s digital transformation initiatives This engagement involved adapting to new business domains while working in a consulting environment.
12/2018 - 11/2019
Postdoc
Technical University of Munich. Munich, Germany

Postdoctoral Researcher

Advanced Mathematical Research & Software Development Continued academic research as a postdoctoral researcher while transitioning expertise toward practical applications in software development and data science. Research Focus Discretization in Geometry and Dynamics Member of SFB Transregio 109 (Collaborative Research Center) Advanced research in computational geometry and dynamic systems Development of novel algorithms for geometric discretization problems Collaboration with international research teams Mathematical Innovation Continued work on non-standard analysis applications Geometric algorithm development and optimization Theoretical foundations for computational geometry software Publication of research findings in peer-reviewed journals Transition to Industry Applications Software Development Leadership Continued leadership of CindyJS: Open Source Project for mathematical visualization Bridge between academic research and practical software applications Development of mathematical software for educational and research purposes Mentoring of PhD students and research assistants Industry Preparation Application of mathematical research to real-world problems Development of skills in practical software development Preparation for transition to industry roles in data science and software engineering This role represented a crucial transition period, allowing me to complete my academic research while developing the practical skills that would define my subsequent industry career in data science and technology leadership.

Experiences