Data Engineer
on demand
(Architecture and civil engineering, 50-250 employees)
Skills
Concise Profile:
I'm a data scientist with more than 5 years of professional experience in academia and industrial applications regarding planning and implementing of cloud-based end-to-end data- and machine learning pipelines. I also have advanced knowledge in researching and modelling of deep learning algorithms. I have particular experience in handling huge amounts of timeseries data for predictive maintenance usecases.
Toolstack (selection):
Python, Scikit-Learn, Spark (Pyspark), Tensorflow, Keras, Scipy, Numpy, Pandas, Koalas, Docker, Azure: Databricks, Deltalake, DataFactory, Mlflow, Flask, Git, Confluence, Plotly Dash,
Jupyter, Java, C++, Andoid, Latex, Linux, MS Office.
What I offer:
Working philosophy:
"Data Science beyond the hype".
My working style is reliable, conscientious and accurate.
I'm a data scientist with more than 5 years of professional experience in academia and industrial applications regarding planning and implementing of cloud-based end-to-end data- and machine learning pipelines. I also have advanced knowledge in researching and modelling of deep learning algorithms. I have particular experience in handling huge amounts of timeseries data for predictive maintenance usecases.
Toolstack (selection):
Python, Scikit-Learn, Spark (Pyspark), Tensorflow, Keras, Scipy, Numpy, Pandas, Koalas, Docker, Azure: Databricks, Deltalake, DataFactory, Mlflow, Flask, Git, Confluence, Plotly Dash,
Jupyter, Java, C++, Andoid, Latex, Linux, MS Office.
What I offer:
- Exploratory data analysis
- Requirements Engineering of data driven products
- Research, implementation, evaluation and quality control of machine learning models
- Design and Implementation of end-to-end data- and machinne learning pipelines
- Clean Code
- Consultation for long term strategies regarding the utilization of data in your business
- Researching and analyzing Usecases regarding their potential businesscase
- Planning and documentation of projects
Working philosophy:
"Data Science beyond the hype".
My working style is reliable, conscientious and accurate.
Project history
12/2022
-
Present
- Strategic planning, maintenance and operation of existing data pipelines from raw data to the dashboard
- Further development, quality assurance and re-implementation of existing ETL pipelines putting special emphasis on data quality
- Development and maintenance of databases
- Establishment of DevOps and DataOps workflows for the automated provision of databases and software modules as well as their implementation and commissioning
- Employee training and knowledge transfer
- Knowledge transfer regarding CI/CD principles and best practices in "handling of data"
- Streamlining of existing software development processes
- Improvement or redesigning parts of the existing data infrastructure
- Giving strategic advice in deciding future software architectures with a special focus on long-term stability, maintainability and ongoing assurance of quality
01/2023
-
03/2023
Data Scientist
on demand
(Automotive and vehicle construction, 1000-5000 employees)
- Planning of machine learning pipelines from development to deployment on ECUs Ensuring long-term maintainability
- Advice on the implementation of quality assurance mechanisms
- Ensuring the model quality, taking into account special platform-related performance drifts
- Exploration and prioritization of modeling approaches for the development of machine learning algorithms for predictive maintenance and wear modeling
- Advice on planning Big Data architectures
04/2022
-
06/2022
Senior Data Manager / Steward
on demand
(Industry and mechanical engineering, >10.000 employees)
- Data lineage automation
- Implementation of data lineage automation solutions
- Lean process management
- Risk analysis
- Projekt requirement analysis
01/2022
-
03/2022
Data Scientist / Data Engineer
on demand
(Automotive and vehicle construction, 1000-5000 employees)
- Development of machine learning approaches for improving precision of quality control at the end of line of production
- Implementing ETL Pipelines using SQL, Pandas
- Migration of sensor data from a legacy system to a skalable datapipeline
- Development of specialized evaluation metrics for quality control of previously developed machine learning models
- Application of those evaluation metrics to field data
- Development of usecases driven by and based on data usage
- Coaching
10/2021
-
12/2021
Machine Learning Engineer
on demand
(Insurance, >10.000 employees)
- Developing machine learning models
- Natural language processing
- Name entity recognition
- Word concept mining
- Improve existing machine learning models
- Migration of data to an Azure Cosmos-DB NoSQL Database
- Evaluating machine learning models
- Machine learning operations
03/2021
-
09/2021
Data Scientist
on demand
(Industry and mechanical engineering, 50-250 employees)
- Consulting and development of strategies to establish a data-driven value chain
- Planning a long-term data infrastructure for sensor data
- Creation of dynamic visualizations
- Creation of concepts for the implementation of future use cases
- First feasibility studies in the form of prototypes
- Development of a machine learning algorithm for fully automatic sensor localization based on Bluetooth echo signatures
01/2019
-
12/2020
Data Scientist / Machine Learning Engineer
on demand
(Automotive and vehicle construction, 1000-5000 employees)
- Researching, implementing and evaluating machine learning models
- Designing, implementing and testing of datapipelines
- Technical planning, development and coordination of machine learning projects in the area of predictive maintenance
- Deployment of machine learning models in live systems
- Acquisition of projects and customers, identification of use cases, cost estimation and bid proposal management
- Data exploration and analysis, project documenation and reporting
- Communication and coordination of project intersections between customer, internal teams and external service providers
- Presenations among the companywide community of experts
02/2018
-
11/2018
Data Scientist
on demand
(Industry and mechanical engineering, < 10 employees)
- Development of a data infrastructure for remote maintenance of tire sensor data
- Extraction, cleaning and aggregation of sensor data from legacy systems
- Transfer of sensor data to a more modern infrastructure
- Exploratory data analysis and statistical root cause analysis of sensor failures
- Development of a monitoring system for monitoring tire conditions for various stakeholders such as fleet managers or maintenance technicians
01/2018
-
03/2018
Data Analyst
on demand
(Internet and Information Technology, 10-50 employees)
- Development of a prototypical data pipeline for data preparation and feature extraction
- Carrying out sanity checks
- Analysis of customer preferences
- Customer segmentation
- Predicting customer churn
- Targeted (data-driven) support of the sales team for customer care
Local Availability
Open to travel worldwide
I am ready to travel.
For some tasks, I prefer remote work but I am happy to negotiate a working mode that works for both parties.
For some tasks, I prefer remote work but I am happy to negotiate a working mode that works for both parties.
