- Collecting customer information needs.
- Processing, cleaning and verifing the integrity of the data used for the analysis.
- Solving non-routine interdisciplinary analysis
problems by applying advanced analytical methods when
- Improving data collection procedures to include relevant information for the construction of analytical systems.
- Taking part on the design and implementation of architectures for the operationalization of the developed models (deploy).
- Carring out ad-hoc analysis and presenting results in a clear way.
- Designing and implementing mechanisms for evaluating and monitoring the models.
- Transfering knowledge about the interpretation and use of the information provided by the developed models.
- Taking training courses and technology certifications related to their tasks.
- Participating and contributing content to the IT Community.
Skills and requirements
- University degree in Systems, Computer Science, Statistics or a related field.
- Solid knowledge on the life cycle of Data Science projects. Excellent command of Analytical techniques such as Machine Learning, Deep Learning and NLP.
- Good command of statistics, including tests and statistical distributions.
- Programming experience (eg Python, R)
- Big data experience (eg Spark, Hadoop)
- Cloud services experience (eg Azure, AWS, IBM)
- Excellent visual, oral and written
- Orientation to results, curiosity, attention to detail.
- Excellent learning and adaptation skills.
- Intermediate level of English
- Experience in reporting and data visualization.
- Experience in management, versioning and code repository.
- Good database query domain (eg, SQL, MySQL).
- Experience with agile management methodologies.