Key responsibilities
- Develop algorithms to forecast, recommend, classify and/or analyse complex datasets
- Participate in the data model definition and refinement to make sure it can be used in ML/AI processes
- Monitor the quality and accuracy of analyses and predictions and develop continuous improvements
- Deploy and operate ML and AI in the cloud, end to end, including ETLs, development of APIs and connectivity to operational databases
Requirements
- Degree in Computer Engineering or similar
- Fluent in English (B2 or higher)
- + 2 years of working experience in a Data Engineering or Data Science based role
- + 1 years of experience in Python, writing not only algorithms but also APIs and applications
- Experience in ETLs, data ingestion pipelines and access to databases
- Experience deploying Python APIs written in Flask or FastAPI
- Experience with technologies like Pandas, NumPy and Sci-kit learn
- Experience developing and operating Jupyter Notebooks, to run code, document processes and display visualisations such as tables and charts
- Experience with ML tools to solve real world problems: sentiment analysis, computer vision, recommender systems, time series analysis, etc.
- Good communication skills
- Familiar with Agile methodologies and Scrum best practices
Nice to have
- Knowledge in Spark and the Hadoop stack
- Knowledge in Keras, Tensorflow
- Knowledge of Docker, CI/CD systems
- Knowledge in AWS, Azure and/or GCP
