Specific qualifications:
- Good knowledge in the Data Science domain:
- Machine Learning algorithms, Statistics and Data Analysis
- Analytics and AI tooling, e.g. Jupyter Notebook, Pandas, Scikit-Learn, PySpark
- Programming languages: Python, R, Scala
- Data Visualization and BI tooling, e.g., Matplotlib, D3.js, Tableau
- Knowledge of IT concepts associated with the deployment of highly scalable systems:
- BigData and distributed processing (Hadoop, Kafka, Spark)
- Cloud native software concepts (serverless and micro-services architectures)
- Experience of building ML use cases in Cloud native platforms E.g. GCP, Azure etc
- Knowledge of IT concepts associated with the software development tools:
- Git and CI/CD pipelines
- Software analysis and design methodologies
- Knowledge of the following subjects is valued:
- Programming languages: R, C++, SQL, Java and JavaScript
- Software quality and security enforcement