PhD CS, Data Science, ML Engineer, Deep Learning
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- 64390 Erzhausen, Hessen
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- 08.04.2024
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"B. hat uns von Anfang an und bis Projektende durch umfassendes Wissen, Organisationstalent, Kundenfokus und Menschenkenntnis begeistert."
2/2021 – 12/2023
Tätigkeitsbeschreibung
o Build the Team, Define Vision and roadmap around the main persona Data Scientist
o Iterate on minimum-viable product (my chosen approach)
o Technical and MLOps aspects of operating hardware/infrastructure, edge-cloud, cloud, and also in development context with CI/CD, considering latency and throughput SLAs required in industrial context
o Participate in concrete Machine Learning projects to implement solution based on the DSP. Mostly in industrial context and research, including monitoring for data drift and general reliability of deployed models
o Most notable a project around our Federated Learning Feature to classify 3D scan for Alzheimer detection in cooperation with Fraunhofer, presented at HannoverMesse, , AI-NET, and eucnc.eu
As edge-first product resource consumption and sharing of GPU resources was a priority. The DSP features we implemented address all aspects of data processing from ingestion in heterogeneous IT landscapes, clean-up and transformation, all the way to hosting and deploying ML models in a privacy preserving fashion. Our unique approach around copy-on-write-snaphots and processing pipelines allowed for Reproducible ML in all workflows, without any lock-in.
Projektleitung / Teamleitung (IT), Continuous Delivery (CDE), DevOps (allg.), ETL, Git, Jira, Kotlin, Maschinelles Lernen, Neuronale Netze, Python, PyTorch, TensorFlow
"B. hat immer eine Lösung gefunden, die uns als Team und unser Produkt besser gemacht hat."
6/2016 – 6/2019
Tätigkeitsbeschreibung
Building Data Science Team for in-house DS department
• Inception and implementation of strategy to begin and iterate DS
projects to maturity in an agile fashion, including getting buy-in
from leadership...
• Coaching new Data Scientist in finding and implementing
appropriate project solutions
Later Product Owner for several projects driven by that strategy and selection from demand funnel with key account manager.
Hands-on implementations
• Implementations for several DS projects in that setting
with python Implementations for computer vision, natural language processing (PDF docs), text entity recognition, table extraction (GPU accelerated Yolo and Faster RCNN), text summarization, sentiment analysis
• Innovative oneshot Siamese CNN solution using keras (tensorflow) for customizable glyph extraction (think checkboxes in scanned docs). Also using OpenCV, pandas, numpy
• Innovative Image Keypoint Detection (like SIFT but for text images) for dewarping scanned Text documents. Using OpenCV, Stable for translation, scaling and rotation
• ID Sequence alignment using Needleman–Wunsch algo
• Sequence Pattern recognition in 2D floating point time series
using sklearn support vector machine (SVM) with sliding
window
• One-off efficient Labeling web-application that saved project only
feasible with supervised learning approach, using flask, nginx,
dash
• Collaboration with DevOps team to create SoA, to provide continuous integration (CI), UI, hosting and abstraction framework for all PwC employees to allow implementation of their own data driven solutions, writing only python code. Kafka for high throughput data delivery, kubernetes and docker for modules
Lean Startup, Maschinelles Lernen, Projektleitung / Teamleitung (IT), Python, SOA (Serviceorientierte Architektur)
Qualifikationen
Projekt‐ & Berufserfahrung
2/2021 – 12/2023
Tätigkeitsbeschreibung
o Build the Team, Define Vision and roadmap around the main persona Data Scientist
o Iterate on minimum-viable product (my chosen approach)
o Technical and MLOps aspects of operating hardware/infrastructure, edge-cloud, cloud, and also in development context with CI/CD, considering latency and throughput SLAs required in industrial context
o Participate in concrete Machine Learning projects to implement solution based on the DSP. Mostly in industrial context and research, including monitoring for data drift and general reliability of deployed models
o Most notable a project around our Federated Learning Feature to classify 3D scan for Alzheimer detection in cooperation with Fraunhofer, presented at HannoverMesse, , AI-NET, and eucnc.eu
As edge-first product resource consumption and sharing of GPU resources was a priority. The DSP features we implemented address all aspects of data processing from ingestion in heterogeneous IT landscapes, clean-up and transformation, all the way to hosting and deploying ML models in a privacy preserving fashion. Our unique approach around copy-on-write-snaphots and processing pipelines allowed for Reproducible ML in all workflows, without any lock-in.
Projektleitung / Teamleitung (IT), Continuous Delivery (CDE), DevOps (allg.), ETL, Git, Jira, Kotlin, Maschinelles Lernen, Neuronale Netze, Python, PyTorch, TensorFlow
7/2017 – 7/2020
Tätigkeitsbeschreibung
Building a Speech Recognition based solution for tax ready drivers log
• Agile, Lean startup based approach around actionable metrics
• Speech Recognition based solution for tax ready drivers log (German tax "Fahrtenbuch") initially with modified one-function-android prototype with GPS tracking and voice recording, later OBD Hardware for car GPS tracker and iPhone app
• Cloud Service for streams of data frames from ioT device (in-car tracker with GPS and milage via OBD2), and voice recordings from mobile app
• Custom Speech Recognition (personal names, in-car noise,...) and dashboard for tax related QA
Big Data, Spracherkennung, Agile Entwicklung, Software Architektur / Modellierung, Amazon Web Services (AWS), Internet of Things (IoT), Projektmanagement
6/2016 – 6/2019
Tätigkeitsbeschreibung
Building Data Science Team for in-house DS department
• Inception and implementation of strategy to begin and iterate DS
projects to maturity in an agile fashion, including getting buy-in
from leadership...
• Coaching new Data Scientist in finding and implementing
appropriate project solutions
Later Product Owner for several projects driven by that strategy and selection from demand funnel with key account manager.
Hands-on implementations
• Implementations for several DS projects in that setting
with python Implementations for computer vision, natural language processing (PDF docs), text entity recognition, table extraction (GPU accelerated Yolo and Faster RCNN), text summarization, sentiment analysis
• Innovative oneshot Siamese CNN solution using keras (tensorflow) for customizable glyph extraction (think checkboxes in scanned docs). Also using OpenCV, pandas, numpy
• Innovative Image Keypoint Detection (like SIFT but for text images) for dewarping scanned Text documents. Using OpenCV, Stable for translation, scaling and rotation
• ID Sequence alignment using Needleman–Wunsch algo
• Sequence Pattern recognition in 2D floating point time series
using sklearn support vector machine (SVM) with sliding
window
• One-off efficient Labeling web-application that saved project only
feasible with supervised learning approach, using flask, nginx,
dash
• Collaboration with DevOps team to create SoA, to provide continuous integration (CI), UI, hosting and abstraction framework for all PwC employees to allow implementation of their own data driven solutions, writing only python code. Kafka for high throughput data delivery, kubernetes and docker for modules
Lean Startup, Maschinelles Lernen, Projektleitung / Teamleitung (IT), Python, SOA (Serviceorientierte Architektur)
10/2010 – 5/2015
Tätigkeitsbeschreibung
(Nokia Location & Commerce), Geographic Information Systems
Lead Engineer and Senior Engineer, Project Management (fulltime employee)
• 3 years team lead for 5 developers, Nokia HERE Geocoding Service (NGC) improvements
Coordination between devs, management, data analysts, testers
Work package definition and prioritization, QA, Code reviews
• Software Development for NGC, 100M requests/day (lucene and proprietary index technology, Java)
• NGC Machine Learning components for query classification (Hidden Markov Model, decision trees)
• Massive parallel data analysis (Hadoop Cloud) applying Machine Learning and statistical approaches to user request analysis for NGC quality improvement (Random Forest, Naive Bayes classifier)
• Project Lead for NGC quality improvements (country Focus)
• Training class instructor for Geodata processing
• Job postings and interviews, onboarding, University liaison (MA thesis,...)
Big Data, Maschinelles Lernen, Projektleitung / Teamleitung (IT), J2EE (Java EE), Software engineering / -technik, Amazon Web Services (AWS)
5/2010 – 10/2010
Tätigkeitsbeschreibung
• Lucene/Solr based search engine for multimedia conference documents (videos, presentation slides, PDFs), portal integration (E-Learning)
• Taxonomy Definition and population using K-Means clustering (Apache Mahout) to categorize conference documents
• Taxonomy for faceted browsing for interactive exploration and refinement
Maschinelles Lernen, Java (allg.)
5/2008 – 4/2010
Tätigkeitsbeschreibung
• Lecturer Information Visualization class, supervisor for master theses, lab assignments and research assignments
• EU-Project ParseInsight project management
• ParseInsight GapAnalysisTool: Dynamic visualization of tree structures in support of methods for analysis and filtering of survey results (Java, Groovy)
• Real-time ridesharing mockup using PTV MobilityPlatform POIAdministration and Routing Service for ADAC. Implementation of Matching (rider to hitcher) component (Java)
• […]: GIS-Module for geographic meta-search engine for carsharing portals: -Hyperlink entfernt- (PHP, PostGis)
• JustGetThere: Mobile Android client for Hopping.de web service with route visualization
• RouteVis3D: Geographic Information System for querying, visualization and manipulation of traffic and route data in systems like Hopping.de. (Java, Java3D, Swing, PostGis)
• OSMRouting: OpenStreetMap based routing module (Java, PostGis)
• OSMConnect: Quality analysis of OpenStreetMap data regarding routing
• IcoPort: Matching and visualization of possibilities for cooperation of delivery services, based on delivery routes and districts for logistics fleet management (PHP, PostGis)
• RideSim: Simulation analysis and visualization of real-time ridesharing systems. Cooperation with TU-Darmstadt and department of transportation/ Hessischem Landesamt für Straßen- und Verkehrswesen (Java, PostGis, Java Topology Suite)
• MapCube: 3D Focus+Context visualization technique for geographic information spaces (Java, JOGL, OpenGL ES) as well as proof of concept for porting to iPhone (C++, OpenGL ES).
• ParseInsight Interactive Map: Google maps based visualization and search of location based project data (PHP, Javascript, Google Maps)
• Consulting myTellus.com (Travel portal; Swedish Centre for International Youth Exchange) regarding integration of GIS visualization- and server components
Grundlagenforschung, Projektleitung / Teamleitung (IT), Software engineering / -technik
5/2006 – 4/2008
Tätigkeitsbeschreibung
Scientific 3D visualization for java applet B2B shop system (LogOn): Mapping of Zeiss lens data to parametric 3D model and tesselation for visualization of glass lenses (Java3D). OpenGL diagnostic tool (C++). LogOn has 15000 users.
• Web services to make prescription calculation logic available to server side business logic. Access .Net and Java web services to integrate wavefront measuring device into LogOn client (Axis, JAX-WS, SOAP)
• Performed Code Review and provide marked up copies to team (8 developers) to improve quality, in particular maintainability of the LogOn system.
• Introduced structured test procedure and test automation for front and back-end components
• Refactoring and redesign of 3-tier architecture of LogOn to improve performance (J2SE, J2EE, JBoss, XML/XSL)
Software engineering / -technik
10/2004 – 10/2005
Tätigkeitsbeschreibung
Embedded Development: Implementation of high-speed eye-tracking to capture saccadic eye movements
Implementation of image processing algorithms for Windows and special purpose hardware (Vision Chip)
Keil 8051 C51, C++
Embedded Entwicklung / hardwarenahe Entwicklung
11/2001 – 4/2006
Tätigkeitsbeschreibung
Continued development and extension of my previous projects and integration with new projects, as well as implementation of new SDServices, troubleshooting and bug fixes (Java, C++)
• Introduced transaction based multithreading model for SDServices (C++)
• GUI extensions for myMissions client, e.g., chat and whiteboard (Java,
Swing)
• Embedded development: Integration of Arula-Box as SDService (8051 C/SDCC small device c compiler)
Software engineering / -technik
11/1999 – 10/2001
Tätigkeitsbeschreibung
Participated in developing distributed system for control and execution of user defined business processes (SDPlatform) based on default and user defined SDProcesses (C++)
• As Lead Senior Software Engineer responsible for requirements analysis and specification, design specification, cost and time estimates, as well as implementation of RecoverSystem, subsystem guaranteeing high availability of SDProcess states (C++)
• Embedded Development: PalmOS Clients for SDPlatform (C++ PalmOS 3.5)
Software engineering / -technik
6/1998 – 9/1999
Tätigkeitsbeschreibung
Contributed to development of „genesis“, a radiosity based 3D rendering system for 5-sided CAVE (immersive virtual reality environment) (C/C++, IrixGL)
• Usability and 3D rendering improvements (C, motif)
• Pre-processing of very large3D models (e.g. Mercedes Benz car models, Frankfurt airport model for Fraport AG) to enable radiosity illumination in genesis
Grafiksoftware (allg.), Objektorientierte Programmierung (OOP), CAE (rechnergestützte Entwicklung / computer-aided engineering)
10/1996 – 9/1998
Tätigkeitsbeschreibung
Requirement analysis and implementation of InsuranceCalculator for calculation and comparison of insurance rates (Visual Basic)
• Design of questionnaire to gather requirements from insurance agents
Objektorientierte Programmierung (OOP)
10/1996 – 9/1998
Tätigkeitsbeschreibung
Implementation of proprietary printer driver for data warehouse system (C/C++, driver programming), as well as data conversion, import/export routines, etc.
• Improving the warehouse inventory software, as well as the end-user software. This involved customization of SAP solutions using ABAP, in particular, mapping the kanban approach of the proprietary solution to SAP functionality.
Software engineering / -technik
Zertifikate
Ausbildung
Darmstadt
Über mich
Building solutions that way has changed a lot over the years, regarding technologies. Not always easier, but definitely more awesome. Massive streams of data from IoT devices along with mobile apps being listened to by ML algorithms to deliver those solutions. Embedded into the user's reality, and using the power of the cloud. That is where I want to be.
It would be my pleasure to help you in building those solutions. I am looking forward to it. Preferably from my home office in the near future :-)
Weitere Kenntnisse
• PhD in Computer Science with emphasis on GPU accelerated 3D graphics and Information Visualization
• Skills and Certifications in Data Science & Artificial Intelligence
• Recently: 3 years Data Science (DS) Team Coach at PriceWaterhouseCoopers
- Building Data Science Team for inhouse DS department
- Machine Learning and AI consulting and implementations
- Computer Vision, Natural Language Processing
- Microservice architecture for Data Insight Platform
• Until 2015: Lead Engineer at Nokia Here with emphasis on
- Data Analytics in Big Data
- Machine Learning
- Architecting improvements for Nokia Here Geocoder (NGC)
• Embedded/IoT: High Speed Eye Tracker, RePhone, 8051, Arduino, Raspberry Pi
=== IN DETAIL ===
MANAGEMENT:
Project and Team lead, CEO role
Always agile since 1999, even without manifesto
Lean startup at heart
TECH:
Data Science & Artificial Intelligence:
• Most work in python, a little R
• Coursera Johns Hopkins University, Data Science Specialization (R)
• Coursera deeplearning.ai, Deep Learning Specialization (python)
• Python, keras, tensorflow, NLTK, spacy, gensim, sklearn, OpenCV, pandas, numpy
• Sequence models, Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU)
• Deep learning for computer vision with Convolutional neural networks (CNN), Yolo, Faster R-CNN
• Semantic search with word2Vec
• Support Vector Machines, k-means, Decision Trees, Classifiers
• Hidden Markov Models in HERE Geocoder (100M requests/day)
• Big Data Random Forest and Naive Bayes for Nokia Geocoder query-log based quality improvement
• Neural networks and genetic algorithms
• Information retrieval, TFID
Agile Software Development Methodologies:
• 5 years Scrum at Nokia,
Daily standups as participant and Scrum master, Scrum-of-Scrums, kanban approaches
Responsible for backlog grooming in lieu with PO
Product Owner Training and PO for 2 projects over 3 years
• 3 years Scrum at PricewaterhouseCoopers, including as PO
More recent additions
• Kubernetes, docker
• Kafka, RabbitMQ, redis
• python flask, dash
• Azure CosmosDB
• Neo4j
• Mobile apps for Android, iOS: Flutter with dart, swift
Ancient
• UML, Enterprise Architect
• Java (J2EE, Swing, JavaFX, Java3D, Netzwerk, JNI, RMI)
• Python
• Groovy
• Pig / hadoop
• R
• Eclipse IDE, IntelliJ IDE, MS Visual Studio, VS Code
• C/C++
• C#
• Embedded-Development (MS embedded VC++, Keil C51, sdcc)
• Metrowerks Codewarrior for PalmOS (C++)
• 3D Visualization with OpenGL, OpenGL ES, Java3D
•
• Mobile: Flutter with dart
• XML/XSL, Axis, JAX-WS
• Turbo Pascal, Delphi
• Perl
• Tcl/Tk
• Lisp
• Visual Basic
• ABAP (SAP)
• Shell scripts
• SQL
• Web: HTML, Javascript (a little CSS)
• TestComplete, SoapUI
• SOAP, JAXB
• JBoss, tomcat, spring
• CVS, Subversion, Git, Maven, Gradle, Bamboo,
• Crucible code reviews
Operating Systems:
• Windows
• Unix (Suse, RedHat, Ubuntu, HP-UX)
• OSX
• Android, iOS
Databases and Infrastructure:
• Postgres (PostGis)
• MongoDB, Azure CosmosDB
• Neo4j
• MySQL
• Oracle
• Access
Miscellaneaous:
• GUI design, web-development, multimedia data formats, data retrieval, Bluetooth
• Administration of Windows and Unix, Firewall, Router, Http-Proxy, networks
Persönliche Daten
- Deutsch (Muttersprache)
- Englisch (Fließend)
- Europäische Union
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