Role overview
We value passion and attitude over experience. Thats why we dont expect you to have every single skill. Instead, weve listed some that we think will help you succeed and grow in this role:
- Degree in computer science or engineering supplemented by extensive training in data science/ML or related disciplines
- Excellent knowledge of Python programming, with software engineering skills including DevOps and CI/CD pipelines
- Experience with Python data science stack (pandas, scikit-learn, keras, numpy, tensorflow)
- Experience in building supervised and unsupervised ML models and in optimizing model (hyper-)parameters tuning for performance and costs
- Strong mathematical skills (probability and statistics, algebra, optimization)
- Knowledge of continuous integration tools and technologies (Jenkins, Ansible, Git)
- Experience with SQL/NoSQL database management
- Experience with LINUX environment (shell scripting)
- Experience with cloud technologies, preferably on Azure
- Experience with containerization and orchestration tools (Docker, Airflow, NiFi, Kubernetes, OpenFaaS) for production
- Experience in MLOps frameworks (e.g. MLFlow and DVC)
- Experience in big data technologies (e.g. Spark, Hadoop, Apache Kafka etc.)
- Proficiency with web APIs development and design (e.g. REST)
- Experience in writing technical documentation
- Agiles procedures
Tags & focus areas
Used for matching and alerts on DevFound Machine Learning Kubernetes Numpy Sql Docker Ansible Tensorflow Git Data Science Mlops