04.11.2024 aktualisiert
60 % verfügbar
Data Scientist | Machine Learning Engineer | Ph.D.
Berlin, Deutschland
Berlin +50 km
Dipl.-Ing. Dr. rer. nat @TU BerlinSkills
data sciencePythonComputer VisionNatural Language ProcessingGCP (Google Cloud Platform)Google Cloud Machine Learning Deep LearningApache AirflowAzure Cloud Data ScienceMLOPS openTelemetry
Building Data/AI Solutions from Research to Scalable Products | Data Science/ML & MLOps Expert
Nico is a Munich(Germany)-based freelancer who specializes in developing data science and machine learning solutions from research to polished product with experience in on-premise and cloud environments.
Nico received his PhD in machine learning from Technical University Berlin and is an author of more than 35 peer-reviewed scientific papers. Having worked for Max Planck Institute, Microsoft Research, Technical University, and the Berlin Center for Machine Learning, he frequently served as a reviewer and program committee member for internationally renowned conferences, workshops, and journals and has extensively collaborated with academic and industrial partners.
Since 2019, he helps companies with his expertise to identify and solve data science and machine learning problems in various roles e.g. CTO, Applications Architect, Data Scientist, or Machine Learning Engineer.
Engineering
>Python, Github, CI/CD, Google Cloud, Azure, Heroku, Digital Ocean
Data science/ML
>Statistics, Machine Learning, LLMs, Neural Networks, Anomaly Detection, Vision, Rule Mining, Optimization
MLOps
>ETL/Airflow, BigQuery/Data Warehouse, Model Tracking, Model Serving, OpenTelemetry/Monitoring
Nico is a Munich(Germany)-based freelancer who specializes in developing data science and machine learning solutions from research to polished product with experience in on-premise and cloud environments.
Nico received his PhD in machine learning from Technical University Berlin and is an author of more than 35 peer-reviewed scientific papers. Having worked for Max Planck Institute, Microsoft Research, Technical University, and the Berlin Center for Machine Learning, he frequently served as a reviewer and program committee member for internationally renowned conferences, workshops, and journals and has extensively collaborated with academic and industrial partners.
Since 2019, he helps companies with his expertise to identify and solve data science and machine learning problems in various roles e.g. CTO, Applications Architect, Data Scientist, or Machine Learning Engineer.
Engineering
>Python, Github, CI/CD, Google Cloud, Azure, Heroku, Digital Ocean
Data science/ML
>Statistics, Machine Learning, LLMs, Neural Networks, Anomaly Detection, Vision, Rule Mining, Optimization
MLOps
>ETL/Airflow, BigQuery/Data Warehouse, Model Tracking, Model Serving, OpenTelemetry/Monitoring
Sprachen
DeutschMutterspracheEnglischverhandlungssicher
Projekthistorie
Morphais is a young quant VC startup that finds and invests in exceptional founders and startups via artificial intelligence and technology. As the CTO, my main responsibilities included:
Tech
- Building a production tech stack for scoring and dealflow
- Building a triple A tech team (Data Scientists, Data Engineers, Developer)
Business
- Hiring and onboarding
- OKRs and corresponding tech KPIs
- Product- and stakeholder management
Tags:
Google Cloud, REST, MLOps, DevOps, Python, Airflow, Data Lake, BigQuery, Cloud Run, Machine Learning, Data Studio, Dashboarding
Tech
- Building a production tech stack for scoring and dealflow
- Building a triple A tech team (Data Scientists, Data Engineers, Developer)
Business
- Hiring and onboarding
- OKRs and corresponding tech KPIs
- Product- and stakeholder management
Tags:
Google Cloud, REST, MLOps, DevOps, Python, Airflow, Data Lake, BigQuery, Cloud Run, Machine Learning, Data Studio, Dashboarding
Conceptualizing, prototyping, and industrialization of a complex cloud-based B2E web application for association rule mining for a big international company of >300k employees. The goal was to enable employees to analyze and find association rules of SAP master data without extensive technical knowledge.
As of end of 2022, the application is still in production and actively used by business analysts around the globe.
The multi-page Python web application is deployed in Azure cloud environment using various services such as ADLS, Web App, DevOps. Besides the data science backend, the application contains extensive visualizations such as charts and tables as well as extensive interactive elements (radio buttons, multi-selects, search, etc) and logic (e.g. Sessions, User and Roles management).
As of end of 2022, the application is still in production and actively used by business analysts around the globe.
The multi-page Python web application is deployed in Azure cloud environment using various services such as ADLS, Web App, DevOps. Besides the data science backend, the application contains extensive visualizations such as charts and tables as well as extensive interactive elements (radio buttons, multi-selects, search, etc) and logic (e.g. Sessions, User and Roles management).