Belén Navarro Martin

AI development application: Develop a medical recommendation engine and chatbot utilizing Vertex AI, combining a recommendation model and search engine to suggest antibiotics based on the target bacteria and considering resistance profiles.

• Machine learning model development and deployment: Utilized Vertex AI to train and deploy a medical recommendation model.
• Conducted user studies to gain insights about the effectiveness of various NLP applications.
• Front-end Development: Adept in front-end development technologies to build user-friendly and responsive interfaces.
• Natural Language Processing (NLP) for healthcare
• High-performance computing (HPC) for:

Training Large Machine Learning Models: analyzing massive datasets of bacterial characteristics, patient information, and treatment outcomes. HPC clusters provide the computational power to train these complex models efficiently.

• Large-Scale Data Processing: HPC can handle the vast amount of data generated by DNA sequencing, antimicrobial susceptibility testing, and electronic health records.
• Simulations and Drug Discovery: HPC can be used to run simulations of how different antibiotics interact with specific bacteria.
• Scalable Inference: Once trained, the AI model needs to be applied to new patient data for real-time recommendations.

Currently

Building AI system for personalized chemo recommendations based on cancer type and affected cells. Currently collecting anonymized patient data (demographics, medical history, treatment response), Cancer Specific Info , Treatment info, Genomic data, Clinical trial data from hospitals and collaborating with researchers to access clinical trial data.

• Concurrently to my roles at Google and Abbott, I undertook international freelance projects as Data Engineer
• Utilized advanced analytics tools such as SAS, SPSS, Excel PowerPivot, to manipulate large volumes of structured and unstructured data sets.
• Managed Azure IaaS and PaaS resources such as SQL Database.
• Created dashboards and visualizations in Tableau or Power BI to monitor key performance indicators.
• Analyzed user requirements, designed and developed ETL processes to load enterprise data into the Data Warehouse.
• Developed and implemented data models, database designs, data access and table maintenance codes.

• Designed and managed data platforms using technologies such as Cloudera, Databricks, and Google BigQuery for data integration between the Cardiac Rhythm Devices.
• Performed complex SQL queries for creating reports using SSRS, Tableau, Power BI, MicroStrategy.
• Designed, developed and tested ETL processes to extract, transform and load data from multiple sources.
• Involved in developing new features for existing applications by analyzing current architecture and implementing enhancements accordingly.
• Developed automated processes for updating datasets used in machine learning projects.
• Integrated existing systems with new platforms such as AWS S3 or Azure Blob Storage.

Mahou : Recommendation engine

•Developed and deployed a scalable recommendation engine for Mahou using Python, machine learning libraries, and cloud platforms.

•Built data pipelines for data acquisition and integration from various sources.

•Implemented recommendation algorithms and optimized engine functionalities.

• Develop key relationships with stakeholders about complex opportunities (MMM, Drive to store, CRM evolutions, API integrations...).
• Provided technical support for clients using the company's products and services.
• Assisted in developing training materials for employees regarding client solutions processes.
• Tested software programs to ensure they meet user requirements.
• Developed strategies for securing networks against unauthorized access.

• Managed data platforms and virtualization infrastructure to support critical business functions.
• Planned, engineered, and supported data center technology to provide protected and safe data storage.
• Developed and implemented a new database system to streamline data storage and retrieval processes.
• Configured and managed databases (both SQL and NoSQL), optimizing data storage and retrieval processes.

• Developed dashboards with Tableau to monitor key performance indicators.
• Utilized advanced analytics tools such as SAS, SPSS, Excel PowerPivot, to manipulate large volumes of structured and unstructured data sets.
• Provided data-driven solutions to support decision making.
• Built visualizations that enabled users to quickly interpret results from complex analyses.
• Maintained documentation of all the processes related to Data Analysis.
• Leveraged SQL queries to extract, transform and load data into databases.