Malte Holmer

- Accelerated a property prediction algorithm by optimizing a convex optimization backend, significantly reducing runtime and memory overhead using python libraries like scipy, numpy and igraph. - Maintained, and modernized the team’s internal CI/CD pipelines, automating testing and deployment workflows using Jenkins. - Designed and built a responsive full-stack web application using a Django backend and Vue.js frontend for complex data and graph visualizations, incorporating Celery for asynchronous execu

- design and implementation of relational databases for storage of time series and operational data using Citus and Postgres - development of production-ready backend code in python, mainly for data processing - execution of data science projects (data analysis, exploration and prediction tasks), including communication with clients from initial kick-off meeting through final presentation

- data analysis, exploration and prediction tasks in the industrial sector - communication with clients, explanation of principles in ML and data acquisition

Data science within the industrial sector: - data exploration and analysis of small- and medium-sized data sets - supervised learning and anomaly detection with shallow learning techniques and neural networks

In-silico toxicology using RDKit, Competitor Analysis using Pandas