Freelancer für Data Science, Machine Learning Engineering and Data Engineering
Aktualisiert am 14.04.2024
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 15.05.2024
Verfügbar zu: 100%
davon vor Ort: 5%
Data Science
Python
Machine Learning
Data Engineering
Machine Learning Engineering
Pandas
Numpy
Spark
Microsoft Azure
AzureML
Databricks
Git
GitHub
DevOps
Docker
SQL
German
native
English
fluent

Einsatzorte

Einsatzorte

Deutschland
möglich

Projekte

Projekte

2 Jahre 2 Monate
2022-01 - 2024-02

Implementation of a Data Science Platform / Migration of Data & Business Processes

Data Engineer / Python Software Engineer Python Atlassian JIRA Atlassian Confluence ...
Data Engineer / Python Software Engineer

  • Team lead (before: Senior Developer) of an agile team of 10 developers practicing SCRUM 
    • Definition, implementation and maintenance of a calculation & validation engine for time-series data including data processing, statistical estimations and forecasting 
    • Development and maintenance of a common function library
    • Migration of data & business processes from the legacy system to the new platform
    • Development of unit tests for all components (engine, library & data / business processes)

    Pandas Numpy Pytest Unittest Kubernetes Camunda
    Python Atlassian JIRA Atlassian Confluence Git Scrum
    4 Monate
    2021-09 - 2021-12

    Design of Chemical Experiments and Formulation Optimization

    Data Scientist
    Data Scientist

    Support product developers in R&D with design of experiments and optimization of chemical formulations using a custom developed software utilizing black-box optimization.

    • Design of Chemical Experiments and Formulation Optimization via Black-Box Optimization
    • Contributed to design and implementation of benchmarking framework to test algorithm candidates
    • Conducted benchmarks on algorithms, documented findings and presented feedback to product team
    • Contributed to code clean-up and major refactoring of codebase
    • Wrote unit tests to increase test coverage

    Python Pandas Numpy Pytest BoTorch Scikit-Optimize Azure ML
    Henkel AG & Co. KGaA
    6 Monate
    2021-07 - 2021-12

    Product Quality Optimization via Machine Learning

    Data Scientist Python Pandas Numpy ...
    Data Scientist

    Optimization of finished good quality utilizing predictive modelling of production process and subsequent optimization of key production parameters.

    • Product Quality Optimization via Machine Learning and Mathematical Optimization

    • Lead data product assessment to evaluate the findings of a previous POC and presented results to stakeholders
    • Conducted exploratory data analysis (EDA)
    • Improved existing data pre-processing
    • Trained predictive models and evaluated their performance
    • Assessed and improved formulation of mathematical optimization problems
    • Repeated EDA, model building and evaluation on new data (additional products)
    • Contributed to setting the scope and estimating budget for the data product

    Python Pandas Numpy Scikit-Learn Matplotlib Gurobi CVXPY Azure ML
    Henkel AG & Co. KGaA
    7 Monate
    2021-01 - 2021-07

    Data Science Toolchain / Platform Standardization

    Data Scientist, Machine Learning Engineer
    Data Scientist, Machine Learning Engineer

    Initiative to standardize the data science toolchain / platform within the team and to provide requirements and feedback for improving the data ecosystem of Henkel in the long-term.

    • Researched machine learning operations approaches and conducted interviews with data scientists in Henkel to gather requirements
    • Exchanged ideas and aligned options with colleagues from the data platform team
    • Conducted an evaluation of Databricks and AzureML against the collected requirements
    • Deployed and configured an experimental AzureML workspace
    • Implemented a demo application with common machine learning tasks like data preprocessing, model training incl. tracking of experiments and versioned model storage
    • Conducted training sessions for the team
    • Contributed to the professionalization and automation of AzureML workspace deployments

    AzureML Databricks Python Pandas Scikit-Learn Spark MLFlow
    Henkel AG & Co. KGaA
    1 Jahr 3 Monate
    2020-01 - 2021-03

    Predictive Credit Risk Assessment (Product)

    Data Scientist, Data Engineer, Machine Learning Engineer, Project Manager
    Data Scientist, Data Engineer, Machine Learning Engineer, Project Manager

    Credit risk assessment of customers based on a machine learning model that

    predicts the probability of default using internally available data. The model is used to complement external rating information for bad-debt provisioning according to IFRS9.

    • Project Management (budget, time booking, security, GDPR and architecture processes)
    • Requirement and stakeholder management
    • Definition of required data sources in collaboration with BI Team
    • Request provisioning of data sources from BI Team including necessary change requests
    • Implementation of the feature extraction pipeline including unit and integration tests in Spark and pytest on Databricks
    • Design and implementation of the machine learning model including probability calibration
    • Detailed model performance analysis
    • Design and implementation of machine learning operations architecture on Azure in close collaboration with the DevOps Team. This included implementation of CI / CD pipelines, scheduling and orchestration of machine learning pipeline using brigade, automated model training on Kubernetes, performance tracking & model versioning in AzureML, logging & alerting using Azure ApplicationInsights and Azure Monitor.
    • Detailed model performance analysis and consultation for expected impact analysis
    • Presentation of concept to external auditors including technical correspondence
    • Hypercare support after go-live
    • In charge of maintenance and operations until end of 2021
    • Presented two live-streamed upskilling sessions about machine learning & AI on the example of this project to an audience of hundreds of internal employees

    Python Pandas Numpy Spark Scikit-Learn XGBoost Pytest Matplotlib Tox Sphinx Databricks AzureML MLFlow Brigade Docker Kubernetes Azure DevOps Pipelines Azure ApplicationInsights Azure Monitor
    Henkel AG & Co. KGaA
    1 Jahr
    2019-01 - 2019-12

    Predictive Credit Risk Assessment (Proof of Concept)

    Data Scientist, Data Engineer, Project Manager
    Data Scientist, Data Engineer, Project Manager

    Credit risk assessment of customers based on a machine learning model that predicts the probability of default using internally available data. The model is intended to replace an existing statistical solution to complement external rating information for bad-debt provisioning according to IFRS9.

    • Project Management (budget, time booking, security, GDPR and architecture processes)
    • Requirement and stakeholder management
    • Defining and requesting data extracts for POC from BI Team
    • Data exploration
    • Data modelling and feature engineering of transactional data
    • Training of machine learning model on unbalanced classes and performance evaluation
    • Communication and presentation of proof-of-concept results to key stakeholders
    • Presentation of concept to external auditors including technical correspondence

    Python Pandas Numpy Spark Scikit-Learn XGBoost MLFlow Docker
    Henkel AG & Co. KGaA
    3 Monate
    2019-07 - 2019-09

    Energy Demand Forecasting

    Data Scientist, Data Engineer
    Data Scientist, Data Engineer

    Energy demand forecasting for optimizing energy procurement. Future energy

    demands of a production line was forecasted using predictive models based on the production schedule and sensor measurements.

    • Requirement and stakeholder management
    • Data exploration and feature engineering
    • Trained time-series machine learning models (using scikit-learn, XGBoost and Prophet) and evaluated their performance
    • Created an interactive dashboard using Plotly Dash which presented insights from the data exploration and visualized the model performance

    Python Pandas Scikit-Learn XGBoost Prophet Matplotlib Plotly Dash
    Henkel AG & Co. KGaA
    8 Monate
    2018-08 - 2019-03

    SalonLab

    Data Scientist, Machine Learning Engineer
    Data Scientist, Machine Learning Engineer

    The SalonLab Smart Analyzer is a handheld device that scans the hair structure through near infrared measurements. Hairdressers use the corresponding SalonLab App in their consultation and analysis process, in which the analysis of the infrared measurements is based on machine learning models to assess hair health.

    • Collaborated in a high-impact projects with multiple external partners and internal teams
    • Consulted on design and development of machine learning models
    • Stress tested a commercial deployment solution for the model prediction microservice
    • Collaborated with a cloud engineer to design an alternative deployment architecture that reduced prediction latencies from seconds to milliseconds. The adoption of the proposed architecture resulted in six figure savings of license costs compared to the commercial deployment solution.
    • Implementation of the model prediction microservice that exposes a REST API developed in Python including logging and error reporting
    • Performed minor changes and upgrades of the API in Dec 2019, Feb 2020, and Jul 2020

    Python Flask Flask RESTplus Gunicorn Pandas Docker Kubernetes JIRA Confluence Apache JMeter
    Henkel AG & Co. KGaA
    4 Monate
    2018-09 - 2018-12

    Smart Accounts Receivables

    Data Scientist, Machine Learning Engineer
    Data Scientist, Machine Learning Engineer

    Optimization of collection efforts by assigning dunning strategies on customer level using a trained classifier.

    • Data extraction from MS SQL source database and data modelling
    • Data exploration
    • Feature engineering to capture customer payment behavior
    • Training of machine learning model on unbalanced classes and performance evaluation
    • Presentation of proof-of-concept results to key stakeholders
    • Mentored colleagues during implementation and roll-out of the product in 2019 / 2020

    Python Pandas Numpy Scikit-Learn Imblearn Matplotlib SQL
    Henkel AG & Co. KGaA
    1 Jahr 4 Monate
    2017-04 - 2018-07

    Qlaym Qoactive Platform

    Data analysis and machine learning platform targeted at the chemical production and healthcare industry providing customizable modules for visualization, data exploration, assisted machine learning modelling, and anomaly detection in an intuitive manner to non-data professionals.

    • Designed and developed a new anomaly detection module for the platform in close collaboration with a UI / UX designer and web developers
    • Developed new capabilities and improved the existing capabilities of the platform?s machine learning backend using Python and MongoDB
    • Contributed to custom module development for customers including translation and parallelization of existing code performing data processing and statistical modelling
    • Contributed to transforming the platform deployment workflow towards using Docker containers and set up CI / CD pipelines with Jenkins
    • Extended the unit- and integration-test suite to increase test coverage
    • Contributed to data pre-processing pipelines for importing and connecting customer?s data sources to the platform

    Python Pandas Numpy Scikit-learn Celery MongoDB Redis RabbitMQ Dask Docker Jenkins SQL (Exasol) Lua Confluence JIRA Git Linux
    Qlaym GmbH
    6 Monate
    2017-07 - 2017-12

    Sales Forecasts for Agricultural Machines

    Data Scientist
    Data Scientist

    Consulting and development of sales forecasts for a customer in the agricultural machinery industry.

    • Consulting the customer on sales forecasting
    • Exploratory data analysis of sales data from multiple business units
    • Development of several machine learning models (Prophet, XGBoost, Scikit Learn) for multiple business units based on historical sales data and external industry indices
    • Performance analysis and comparison of the models
    • Presentation of the results to the customer

    Python Pandas Numpy Scikit-learn Prophet XGBoost Matplotlib Seaborn
    Qlaym GmbH
    2 Monate
    2017-10 - 2017-11

    Data Exploration and Anomaly Detection for an Industrial Process Plant

    Data Scientist
    Data Scientist

    Consulting, exploratory data analysis and anomaly detection on production monitoring data from an industrial process plant for a customer in the plant building industry.

    • Consulting the customer on topics of anomaly detection and predictive maintenance
    • Exploratory data analysis of production monitoring data
    • Anomaly detection on production monitoring data
    • Data pre-processing and data import to the Qlaym Qoactive Platform (see below)

    Python Pandas Numpy Scikit-learn Matplotlib Seaborn
    Qlaym GmbH

    Aus- und Weiterbildung

    Aus- und Weiterbildung

    4 Jahre 8 Monate
    2011-07 - 2016-02

    Electrical Engineering and Information Technology

    Dr.-Ing., RWTH Aachen University, Aachen, Germany
    Dr.-Ing.
    RWTH Aachen University, Aachen, Germany

    • ?Eigenvalue-Based Spectrum Sensing for Cognitive Radio: Change Detection Problems and Fundamental Performance Limits?
    • Statistical hypothesis testing for signal detection in wireless communications

    5 Jahre 9 Monate
    2005-10 - 2011-06

    Computer Engineering (equivalent to Master of Science)

    Diplom Ingenieur, RWTH Aachen University, Aachen, Germany
    Diplom Ingenieur
    RWTH Aachen University, Aachen, Germany
    • ?Development of a fully digital FPGA based magnetic induction measurement system?
    • Signal processing, wireless communications, and medical technology Graduated in top 20 % of Computer Engineering graduates of the academic year

    Position

    Position

    Freelancer for Data Science, Machine Learning Engineering and Data Engineering with strong Software Engineering skills. Industry experience in (in-house) consulting and leading data science projects through the entire product life cycle from ideation, proof-of-concept to bringing data products into production in the cloud.

    Kompetenzen

    Kompetenzen

    Top-Skills

    Data Science Python Machine Learning Data Engineering Machine Learning Engineering Pandas Numpy Spark Microsoft Azure AzureML Databricks Git GitHub DevOps Docker SQL

    Produkte / Standards / Erfahrungen / Methoden

    Profile

    Senior Data Scientist with a PhD in Electrical Engineering, having extensive experience in leading machine learning POCs and projects through the entire product life cycle: 

    • use case ideation, feasibility study implementation and bringing models into production using cloud services


    Professional Experience

    2022-01 - heute

    Role: Freelancer


    Tasks:

    • Freelancer for Data Science, Machine Learning Engineering and Data Engineering See project list below for further details


    2018-08 - 2021-12

    Role: Senior Data Scientist

    Customer: Henkel AG & Co. KGaA, Düsseldorf, Germany


    Tasks:

    In-house Data Science consulting covering a broad range of use-cases across the organization

    • Lead and contributed to several Data Science / machine learning POCs and projects with different business contexts: customer credit risk assessment, smart debt collection, product quality optimization, chemical experiment design and formulation optimization, energy demand forecasting, hair health assessment from sensor measurements, etc.
    • Mentored junior data scientists in multiple projects on problems concerning machine learning techniques, infrastructure, deployment, and scaling
    • Consulted data science use-cases in the ideation phase and conducted quality assurance on projects with external implementation partners in all phases of the project lifecycle
    • Lead an initiative to standardize the team internal data science toolchain. This included requirement analysis, evaluation of platform options (AzureML and Databricks), deploying and configuring an experimental AzureML environment, creating a demo application and conducting training sessions for the team. Contributed to automation of AzureML workspace deployment
    • Advocated the application of principles from software engineering and DevOps in machine learning projects. Pioneered Spark (Databricks) CI / CD workflows including unit and integration testing in close collaboration with Henkel?s DevOps team
    • Contributed to the digital upskilling within the Finance department with two separate presentations about machine learning use-cases in Finance that were broadcasted to hundreds of Henkel?s employees
    • Created a data challenge that was used as part of the recruitment process for the team and regularly assisted and conducted technical interviews


    Skills:

    Python, Pandas, Numpy, Scikit-learn, XGBoost, Spark, Databricks, Prophet, MLflow, Azure ML, Matplotlib, Seaborn, Plotly dash, BoTorch, Scikit-Optimize, MS SQL, Docker, Kubernetes, Brigade, Azure, Azure DevOps Pipelines, Git, Linux, MacOS


    2017-04 - 2018-07

    Role: Data Scientist

    Customer: Qlaym GmbH, Düsseldorf, Germany


    Tasks:

    Data Science consulting and machine learning backend development in a data science startup

    • Exploratory data analysis of customer data such as financial time-series and sensor data from chemical production plants
    • Built time-series forecasting models to predict sales for a customer in the agricultural sector
    • Developed a new anomaly detection sub-module for the in-house data science platform
    • Development for the machine learning backend of the in-house data science platform
    • Setup and maintenance of continuous integration (CI) for the in-house data science platform with Jenkins and Docker
    • Contributed to the Dask open-source project by reporting and fixing bugs


    Skills:

    Python, Pandas, Numpy, Scikit-learn, XGBoost, Prophet, Matplotlib, Seaborn, Dask, Celery, Docker, Jenkins, MongoDB, SQL (Exasol), Redis, RabbitMQ, Lua, Kafka, Git, Linux


    2011-12 - 2017-03

    Role: Scientific Staff

    Customer: RWTH Aachen University, Aachen, Germany


    Tasks:

    Performed research on detection algorithms for wireless communications and bio-inspired information processing in the Institute for Theoretical Information Technology

    • Supervised master and bachelor theses as well as student research assistants
    • Analysis of large datasets and distributed Monte Carlo simulations
    • Statistical hypothesis testing, detection and estimation theory, signal processing
    • Information theory, stochastics, convex optimization, linear algebra, compressed sensing


    Skills:

    MATLAB, Python, C, LaTex, Git, Linux, MacOS


    2011-06 - 2011-11

    Role: Graduate Research Assistant

    Customer: RWTH Aachen University, Germany


    Tasks:

    • Developed improvements for a fully digital magnetic induction measurement system originally developed during my diploma thesis at the Chair for Medical Information Technology.


    Skills:

    C / C++, Python, VHDL, Electronics


    2009-11 - 2010-04

    Role: Intern

    Customer: Philips Electronics Netherlands B.V., Eindhoven, Netherlands


    Tasks:

    • Participated in a Neonatal Monitoring research project in the Biomedical Sensor Systems group
    • The work consisted of drafting of electronic hardware specifications, hardware development and development of a C++ framework for acquisition, processing and analyzing multiple sensor data sources


    Skills:

    C++, Cern ROOT, Electronics


    2007 - 2009

    Role: Student Research Assistant,

    Customer: RWTH Aachen University, Aachen, Germany


    Tasks:

    • Chair for Medical Information Technology: Analog and digital hardware development for a magnetic induction measurement system. (Technologies: Electronics, Programmable Logic)
    • Chair of Railway Engineering and Transport Economics: Software development for a railway capacity allocation simulator.


    Skills:

    C++

    Einsatzorte

    Einsatzorte

    Deutschland
    möglich

    Projekte

    Projekte

    2 Jahre 2 Monate
    2022-01 - 2024-02

    Implementation of a Data Science Platform / Migration of Data & Business Processes

    Data Engineer / Python Software Engineer Python Atlassian JIRA Atlassian Confluence ...
    Data Engineer / Python Software Engineer

    • Team lead (before: Senior Developer) of an agile team of 10 developers practicing SCRUM 
      • Definition, implementation and maintenance of a calculation & validation engine for time-series data including data processing, statistical estimations and forecasting 
      • Development and maintenance of a common function library
      • Migration of data & business processes from the legacy system to the new platform
      • Development of unit tests for all components (engine, library & data / business processes)

      Pandas Numpy Pytest Unittest Kubernetes Camunda
      Python Atlassian JIRA Atlassian Confluence Git Scrum
      4 Monate
      2021-09 - 2021-12

      Design of Chemical Experiments and Formulation Optimization

      Data Scientist
      Data Scientist

      Support product developers in R&D with design of experiments and optimization of chemical formulations using a custom developed software utilizing black-box optimization.

      • Design of Chemical Experiments and Formulation Optimization via Black-Box Optimization
      • Contributed to design and implementation of benchmarking framework to test algorithm candidates
      • Conducted benchmarks on algorithms, documented findings and presented feedback to product team
      • Contributed to code clean-up and major refactoring of codebase
      • Wrote unit tests to increase test coverage

      Python Pandas Numpy Pytest BoTorch Scikit-Optimize Azure ML
      Henkel AG & Co. KGaA
      6 Monate
      2021-07 - 2021-12

      Product Quality Optimization via Machine Learning

      Data Scientist Python Pandas Numpy ...
      Data Scientist

      Optimization of finished good quality utilizing predictive modelling of production process and subsequent optimization of key production parameters.

      • Product Quality Optimization via Machine Learning and Mathematical Optimization

      • Lead data product assessment to evaluate the findings of a previous POC and presented results to stakeholders
      • Conducted exploratory data analysis (EDA)
      • Improved existing data pre-processing
      • Trained predictive models and evaluated their performance
      • Assessed and improved formulation of mathematical optimization problems
      • Repeated EDA, model building and evaluation on new data (additional products)
      • Contributed to setting the scope and estimating budget for the data product

      Python Pandas Numpy Scikit-Learn Matplotlib Gurobi CVXPY Azure ML
      Henkel AG & Co. KGaA
      7 Monate
      2021-01 - 2021-07

      Data Science Toolchain / Platform Standardization

      Data Scientist, Machine Learning Engineer
      Data Scientist, Machine Learning Engineer

      Initiative to standardize the data science toolchain / platform within the team and to provide requirements and feedback for improving the data ecosystem of Henkel in the long-term.

      • Researched machine learning operations approaches and conducted interviews with data scientists in Henkel to gather requirements
      • Exchanged ideas and aligned options with colleagues from the data platform team
      • Conducted an evaluation of Databricks and AzureML against the collected requirements
      • Deployed and configured an experimental AzureML workspace
      • Implemented a demo application with common machine learning tasks like data preprocessing, model training incl. tracking of experiments and versioned model storage
      • Conducted training sessions for the team
      • Contributed to the professionalization and automation of AzureML workspace deployments

      AzureML Databricks Python Pandas Scikit-Learn Spark MLFlow
      Henkel AG & Co. KGaA
      1 Jahr 3 Monate
      2020-01 - 2021-03

      Predictive Credit Risk Assessment (Product)

      Data Scientist, Data Engineer, Machine Learning Engineer, Project Manager
      Data Scientist, Data Engineer, Machine Learning Engineer, Project Manager

      Credit risk assessment of customers based on a machine learning model that

      predicts the probability of default using internally available data. The model is used to complement external rating information for bad-debt provisioning according to IFRS9.

      • Project Management (budget, time booking, security, GDPR and architecture processes)
      • Requirement and stakeholder management
      • Definition of required data sources in collaboration with BI Team
      • Request provisioning of data sources from BI Team including necessary change requests
      • Implementation of the feature extraction pipeline including unit and integration tests in Spark and pytest on Databricks
      • Design and implementation of the machine learning model including probability calibration
      • Detailed model performance analysis
      • Design and implementation of machine learning operations architecture on Azure in close collaboration with the DevOps Team. This included implementation of CI / CD pipelines, scheduling and orchestration of machine learning pipeline using brigade, automated model training on Kubernetes, performance tracking & model versioning in AzureML, logging & alerting using Azure ApplicationInsights and Azure Monitor.
      • Detailed model performance analysis and consultation for expected impact analysis
      • Presentation of concept to external auditors including technical correspondence
      • Hypercare support after go-live
      • In charge of maintenance and operations until end of 2021
      • Presented two live-streamed upskilling sessions about machine learning & AI on the example of this project to an audience of hundreds of internal employees

      Python Pandas Numpy Spark Scikit-Learn XGBoost Pytest Matplotlib Tox Sphinx Databricks AzureML MLFlow Brigade Docker Kubernetes Azure DevOps Pipelines Azure ApplicationInsights Azure Monitor
      Henkel AG & Co. KGaA
      1 Jahr
      2019-01 - 2019-12

      Predictive Credit Risk Assessment (Proof of Concept)

      Data Scientist, Data Engineer, Project Manager
      Data Scientist, Data Engineer, Project Manager

      Credit risk assessment of customers based on a machine learning model that predicts the probability of default using internally available data. The model is intended to replace an existing statistical solution to complement external rating information for bad-debt provisioning according to IFRS9.

      • Project Management (budget, time booking, security, GDPR and architecture processes)
      • Requirement and stakeholder management
      • Defining and requesting data extracts for POC from BI Team
      • Data exploration
      • Data modelling and feature engineering of transactional data
      • Training of machine learning model on unbalanced classes and performance evaluation
      • Communication and presentation of proof-of-concept results to key stakeholders
      • Presentation of concept to external auditors including technical correspondence

      Python Pandas Numpy Spark Scikit-Learn XGBoost MLFlow Docker
      Henkel AG & Co. KGaA
      3 Monate
      2019-07 - 2019-09

      Energy Demand Forecasting

      Data Scientist, Data Engineer
      Data Scientist, Data Engineer

      Energy demand forecasting for optimizing energy procurement. Future energy

      demands of a production line was forecasted using predictive models based on the production schedule and sensor measurements.

      • Requirement and stakeholder management
      • Data exploration and feature engineering
      • Trained time-series machine learning models (using scikit-learn, XGBoost and Prophet) and evaluated their performance
      • Created an interactive dashboard using Plotly Dash which presented insights from the data exploration and visualized the model performance

      Python Pandas Scikit-Learn XGBoost Prophet Matplotlib Plotly Dash
      Henkel AG & Co. KGaA
      8 Monate
      2018-08 - 2019-03

      SalonLab

      Data Scientist, Machine Learning Engineer
      Data Scientist, Machine Learning Engineer

      The SalonLab Smart Analyzer is a handheld device that scans the hair structure through near infrared measurements. Hairdressers use the corresponding SalonLab App in their consultation and analysis process, in which the analysis of the infrared measurements is based on machine learning models to assess hair health.

      • Collaborated in a high-impact projects with multiple external partners and internal teams
      • Consulted on design and development of machine learning models
      • Stress tested a commercial deployment solution for the model prediction microservice
      • Collaborated with a cloud engineer to design an alternative deployment architecture that reduced prediction latencies from seconds to milliseconds. The adoption of the proposed architecture resulted in six figure savings of license costs compared to the commercial deployment solution.
      • Implementation of the model prediction microservice that exposes a REST API developed in Python including logging and error reporting
      • Performed minor changes and upgrades of the API in Dec 2019, Feb 2020, and Jul 2020

      Python Flask Flask RESTplus Gunicorn Pandas Docker Kubernetes JIRA Confluence Apache JMeter
      Henkel AG & Co. KGaA
      4 Monate
      2018-09 - 2018-12

      Smart Accounts Receivables

      Data Scientist, Machine Learning Engineer
      Data Scientist, Machine Learning Engineer

      Optimization of collection efforts by assigning dunning strategies on customer level using a trained classifier.

      • Data extraction from MS SQL source database and data modelling
      • Data exploration
      • Feature engineering to capture customer payment behavior
      • Training of machine learning model on unbalanced classes and performance evaluation
      • Presentation of proof-of-concept results to key stakeholders
      • Mentored colleagues during implementation and roll-out of the product in 2019 / 2020

      Python Pandas Numpy Scikit-Learn Imblearn Matplotlib SQL
      Henkel AG & Co. KGaA
      1 Jahr 4 Monate
      2017-04 - 2018-07

      Qlaym Qoactive Platform

      Data analysis and machine learning platform targeted at the chemical production and healthcare industry providing customizable modules for visualization, data exploration, assisted machine learning modelling, and anomaly detection in an intuitive manner to non-data professionals.

      • Designed and developed a new anomaly detection module for the platform in close collaboration with a UI / UX designer and web developers
      • Developed new capabilities and improved the existing capabilities of the platform?s machine learning backend using Python and MongoDB
      • Contributed to custom module development for customers including translation and parallelization of existing code performing data processing and statistical modelling
      • Contributed to transforming the platform deployment workflow towards using Docker containers and set up CI / CD pipelines with Jenkins
      • Extended the unit- and integration-test suite to increase test coverage
      • Contributed to data pre-processing pipelines for importing and connecting customer?s data sources to the platform

      Python Pandas Numpy Scikit-learn Celery MongoDB Redis RabbitMQ Dask Docker Jenkins SQL (Exasol) Lua Confluence JIRA Git Linux
      Qlaym GmbH
      6 Monate
      2017-07 - 2017-12

      Sales Forecasts for Agricultural Machines

      Data Scientist
      Data Scientist

      Consulting and development of sales forecasts for a customer in the agricultural machinery industry.

      • Consulting the customer on sales forecasting
      • Exploratory data analysis of sales data from multiple business units
      • Development of several machine learning models (Prophet, XGBoost, Scikit Learn) for multiple business units based on historical sales data and external industry indices
      • Performance analysis and comparison of the models
      • Presentation of the results to the customer

      Python Pandas Numpy Scikit-learn Prophet XGBoost Matplotlib Seaborn
      Qlaym GmbH
      2 Monate
      2017-10 - 2017-11

      Data Exploration and Anomaly Detection for an Industrial Process Plant

      Data Scientist
      Data Scientist

      Consulting, exploratory data analysis and anomaly detection on production monitoring data from an industrial process plant for a customer in the plant building industry.

      • Consulting the customer on topics of anomaly detection and predictive maintenance
      • Exploratory data analysis of production monitoring data
      • Anomaly detection on production monitoring data
      • Data pre-processing and data import to the Qlaym Qoactive Platform (see below)

      Python Pandas Numpy Scikit-learn Matplotlib Seaborn
      Qlaym GmbH

      Aus- und Weiterbildung

      Aus- und Weiterbildung

      4 Jahre 8 Monate
      2011-07 - 2016-02

      Electrical Engineering and Information Technology

      Dr.-Ing., RWTH Aachen University, Aachen, Germany
      Dr.-Ing.
      RWTH Aachen University, Aachen, Germany

      • ?Eigenvalue-Based Spectrum Sensing for Cognitive Radio: Change Detection Problems and Fundamental Performance Limits?
      • Statistical hypothesis testing for signal detection in wireless communications

      5 Jahre 9 Monate
      2005-10 - 2011-06

      Computer Engineering (equivalent to Master of Science)

      Diplom Ingenieur, RWTH Aachen University, Aachen, Germany
      Diplom Ingenieur
      RWTH Aachen University, Aachen, Germany
      • ?Development of a fully digital FPGA based magnetic induction measurement system?
      • Signal processing, wireless communications, and medical technology Graduated in top 20 % of Computer Engineering graduates of the academic year

      Position

      Position

      Freelancer for Data Science, Machine Learning Engineering and Data Engineering with strong Software Engineering skills. Industry experience in (in-house) consulting and leading data science projects through the entire product life cycle from ideation, proof-of-concept to bringing data products into production in the cloud.

      Kompetenzen

      Kompetenzen

      Top-Skills

      Data Science Python Machine Learning Data Engineering Machine Learning Engineering Pandas Numpy Spark Microsoft Azure AzureML Databricks Git GitHub DevOps Docker SQL

      Produkte / Standards / Erfahrungen / Methoden

      Profile

      Senior Data Scientist with a PhD in Electrical Engineering, having extensive experience in leading machine learning POCs and projects through the entire product life cycle: 

      • use case ideation, feasibility study implementation and bringing models into production using cloud services


      Professional Experience

      2022-01 - heute

      Role: Freelancer


      Tasks:

      • Freelancer for Data Science, Machine Learning Engineering and Data Engineering See project list below for further details


      2018-08 - 2021-12

      Role: Senior Data Scientist

      Customer: Henkel AG & Co. KGaA, Düsseldorf, Germany


      Tasks:

      In-house Data Science consulting covering a broad range of use-cases across the organization

      • Lead and contributed to several Data Science / machine learning POCs and projects with different business contexts: customer credit risk assessment, smart debt collection, product quality optimization, chemical experiment design and formulation optimization, energy demand forecasting, hair health assessment from sensor measurements, etc.
      • Mentored junior data scientists in multiple projects on problems concerning machine learning techniques, infrastructure, deployment, and scaling
      • Consulted data science use-cases in the ideation phase and conducted quality assurance on projects with external implementation partners in all phases of the project lifecycle
      • Lead an initiative to standardize the team internal data science toolchain. This included requirement analysis, evaluation of platform options (AzureML and Databricks), deploying and configuring an experimental AzureML environment, creating a demo application and conducting training sessions for the team. Contributed to automation of AzureML workspace deployment
      • Advocated the application of principles from software engineering and DevOps in machine learning projects. Pioneered Spark (Databricks) CI / CD workflows including unit and integration testing in close collaboration with Henkel?s DevOps team
      • Contributed to the digital upskilling within the Finance department with two separate presentations about machine learning use-cases in Finance that were broadcasted to hundreds of Henkel?s employees
      • Created a data challenge that was used as part of the recruitment process for the team and regularly assisted and conducted technical interviews


      Skills:

      Python, Pandas, Numpy, Scikit-learn, XGBoost, Spark, Databricks, Prophet, MLflow, Azure ML, Matplotlib, Seaborn, Plotly dash, BoTorch, Scikit-Optimize, MS SQL, Docker, Kubernetes, Brigade, Azure, Azure DevOps Pipelines, Git, Linux, MacOS


      2017-04 - 2018-07

      Role: Data Scientist

      Customer: Qlaym GmbH, Düsseldorf, Germany


      Tasks:

      Data Science consulting and machine learning backend development in a data science startup

      • Exploratory data analysis of customer data such as financial time-series and sensor data from chemical production plants
      • Built time-series forecasting models to predict sales for a customer in the agricultural sector
      • Developed a new anomaly detection sub-module for the in-house data science platform
      • Development for the machine learning backend of the in-house data science platform
      • Setup and maintenance of continuous integration (CI) for the in-house data science platform with Jenkins and Docker
      • Contributed to the Dask open-source project by reporting and fixing bugs


      Skills:

      Python, Pandas, Numpy, Scikit-learn, XGBoost, Prophet, Matplotlib, Seaborn, Dask, Celery, Docker, Jenkins, MongoDB, SQL (Exasol), Redis, RabbitMQ, Lua, Kafka, Git, Linux


      2011-12 - 2017-03

      Role: Scientific Staff

      Customer: RWTH Aachen University, Aachen, Germany


      Tasks:

      Performed research on detection algorithms for wireless communications and bio-inspired information processing in the Institute for Theoretical Information Technology

      • Supervised master and bachelor theses as well as student research assistants
      • Analysis of large datasets and distributed Monte Carlo simulations
      • Statistical hypothesis testing, detection and estimation theory, signal processing
      • Information theory, stochastics, convex optimization, linear algebra, compressed sensing


      Skills:

      MATLAB, Python, C, LaTex, Git, Linux, MacOS


      2011-06 - 2011-11

      Role: Graduate Research Assistant

      Customer: RWTH Aachen University, Germany


      Tasks:

      • Developed improvements for a fully digital magnetic induction measurement system originally developed during my diploma thesis at the Chair for Medical Information Technology.


      Skills:

      C / C++, Python, VHDL, Electronics


      2009-11 - 2010-04

      Role: Intern

      Customer: Philips Electronics Netherlands B.V., Eindhoven, Netherlands


      Tasks:

      • Participated in a Neonatal Monitoring research project in the Biomedical Sensor Systems group
      • The work consisted of drafting of electronic hardware specifications, hardware development and development of a C++ framework for acquisition, processing and analyzing multiple sensor data sources


      Skills:

      C++, Cern ROOT, Electronics


      2007 - 2009

      Role: Student Research Assistant,

      Customer: RWTH Aachen University, Aachen, Germany


      Tasks:

      • Chair for Medical Information Technology: Analog and digital hardware development for a magnetic induction measurement system. (Technologies: Electronics, Programmable Logic)
      • Chair of Railway Engineering and Transport Economics: Software development for a railway capacity allocation simulator.


      Skills:

      C++

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