Python Developer - Gov Tech Energysector
(Energie, Wasser und Umwelt, 1000-5000 Mitarbeiter)
Schlagwörter
Skills
CV bullets
Data platforms (including Data Engineering, Data Science, Data Analysis, ML) Applied mathematics, Optimization, Python backend, Cloud programming
Primary programming languages:
Python, SQL (different dialects)
IT Frameworks: dbt, airflow, airbyte, Google cloud, prefect, streamlit, jupyter, sqlmesh, numpy, scipy, pandas, scikit-learn, scikit-image, pytorch, tensorflow, keras, dash, plotly, matplotlib, fastapi, flask, poetry, conda, venv, Google-OR, optaplanner, bootstrap, fenics, pyspark, sql, xml, json, pytest,...
General:
git, github actions, github, gitlab, CI & CD, docker, bash,...
- 2016: MSc in Applied Mathematics (University of Bremen)
- 2019: PhD in Data Science/Machine Learning (University of Oslo)
- 2020 - ...: Consultant for Data platforms (Machine Learning, Data Science, Data Engineering), Python development
- 2021 - ...: Freelancing
Data platforms (including Data Engineering, Data Science, Data Analysis, ML) Applied mathematics, Optimization, Python backend, Cloud programming
Primary programming languages:
Python, SQL (different dialects)
IT Frameworks: dbt, airflow, airbyte, Google cloud, prefect, streamlit, jupyter, sqlmesh, numpy, scipy, pandas, scikit-learn, scikit-image, pytorch, tensorflow, keras, dash, plotly, matplotlib, fastapi, flask, poetry, conda, venv, Google-OR, optaplanner, bootstrap, fenics, pyspark, sql, xml, json, pytest,...
General:
git, github actions, github, gitlab, CI & CD, docker, bash,...
Projekthistorie
11/2023
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bis jetzt
09/2021
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bis jetzt
Data platform developer - Real Estate Broker
Real Estate Broker
(Architektur und Bauwesen, 10-50 Mitarbeiter)
In this project I am responsible for setting up a cloud-based data infrastructure behind a commercial real estate data analytics platform. The work includes all types of data work, namely research of data sources, data pipelining, modeling, and enrichment through collaboration with commercial real estate domain experts. I heavily rely on tools of the modern data stack in this project: airflow, dbt, prefect, streamlit, airbyte. Furthermore, I'm using fastapi for developing an API and docker, GCP, github actions for cloud delivery and CI/CD.
06/2023
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11/2023
Machine Learning Engineer - Legal Tech Scaleup
Legal Tech Scaleup
(Wirtschaftsprüfung, Steuern und Recht, 50-250 Mitarbeiter)
In this project I am developing a lead scoring algorithm for a legal tech scaleup that helps them prioritze potential case based on their chance of being a successful case. I'm using Snowflake, dbt, and SQL for developing good data models that serve as input to the ML models developed in the Python ecosystem (scikit-learn, pandas, plotly). I use streamlit to visualize and explain the results to key stakeholders in the project.
06/2021
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09/2021
Data Analyst - Biotech Startup
Biotech Startup
(Pharma und Medizintechnik, < 10 Mitarbeiter)
I work as a data scientist with drug screening data for finding novel treatment strategies against certain types of cancer. The data consists of drug-response curves for novel drug combinations, and the main goal is to identify potential drug synergies based on features derived from commonly used drug interactions models. I further build a dashboard app based on Dash and Plotly to visualize experimental data and analysis, running in the background, in an interactive manner.
Tech: Python, Pandas, Dash, Git, Azure, Microsoft Teams
Tech: Python, Pandas, Dash, Git, Azure, Microsoft Teams
02/2021
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05/2021
Operation Research Scientist - Logistics Scaleup
Logistics scaleup
(Transport und Logistik, 10-50 Mitarbeiter)
Based on stakeholder’s interests in typical delivery routes, I have conceptualized and implemented an algorithm for solving time-constrained vehicle routing optimization problems using the Google OR and OptaPlanner software framework. The primary programming languages were Kotlin (OptaPlanner framework) and Python (Google OR). The solver is designed for large scale problems, handling thousands of scheduled visits per day.
Tech: Java, Kotlin, OptaPlanner, Google OR, XML, JSON
Tech: Java, Kotlin, OptaPlanner, Google OR, XML, JSON
03/2020
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09/2020
Data Scientist - Governmal Health Institute
Governmental health institute
(Internet und Informationstechnologie, 10-50 Mitarbeiter)
As a member of the data science team of the Norwegian Corona tracing app ‘Smittestopp’, I developed the backend for the data analysis pipeline and algorithms, which were tailored to identify contacts between individuals based on geospatial data (GPS) and Bluetooth data. The primary backend language was Python. The data was stored in MS SQL data bases. Due to the large amount of streaming data, database design was of key importance to facilitate fast queries within from the Python backend. We further used real-world test scenarios to measure the reliability and quality of the tracing app. These findings are published as a report on the Simula webpage as well as in an upcoming Springer book.
Tech: Python, Microsoft SQL, Azure, Jira
Tech: Python, Microsoft SQL, Azure, Jira
Reisebereitschaft
In der Stadt Hamburg mit einem Radius von 25 km verfügbar
