Professional position for developing the datapipeline of the company and providing support to the data team in engineering related tasks

• Design and development of the main data pipeline as well as the data warehouse solution using Redshift
• Development of best practices in the python code (TDD, PR, DDD, concurrency, brokers, continuous integration, team communication, etc.) within the Data team.
• Development of a rest API for consuming scientific scripts.
• Management of AWS services using serverless and ansible
• In charge of providing basic setup for BI tools (Tableau and Quicksight) and more detailed analysis using Pandas, Dash and

Professional position for developing models that predict key performance indicators and allocation of investments in the marketing field.

• Design and development together with other colleages of data pipelines and models that capture marketing features. Outliers detection, data cleaning, and enssemble learning.
• Implementation and maintenance of linear and non-linear models using the standards of scikit-learn for regression. This include all the steps of the machine learning pipeline. Use of Numpy, Scipy, Matplotlib and Statsmodels for the analysis of the whole design.
• Interaction with the Amazon Web Services using Boto3 (python SDK) library to access different kind of resources (S3, DynamoDB, CloudFormation).
• Implementation of basic features/solutions for the back-end and front-end based on javascript to show the customer the results of the predictions and other features of the models.

Doctoral position to study the dynamics between the cortical areas and the parahippocampal areas during sleep and their effect on memory consolidation. This involves different areas of knowledge:

• Signal processing, using Matlab and Python (scipy, numpy, pandas, etc.) to get multitaper- spectrograms, signal whitening, Hilbert transform, causal filters, wavelet-transform.
• Machine learning, using supervised and unsupervised techniques as PCA, ICA, Gaussian Mixture Models, logistic regression, neural networks.
• Involved in the Braincomm project.

Applying signal processing and machine learning techniques on electrophysiology data.

Testing engineer at Daimler factory in Sindelfingen.

• Developer of new functionalities for automatic tests through the OBD on-board diagnosis protocol. Classification and tracking of the DTC (diagnostic trouble codes) related mainly with the automatic on-road assistance project.
• Developer of different functionalities and test cases in C# for the internal testing framework.

One year internship to work on my master thesis. The final project was related to the development of new diagnosis features for telematic applications in the car.