Sebastián holds a PhD in Machine Learning and Data Science, accompanied by 10+ years of experience managing interdisciplinary projects across various sectors like medicine, banking, marketing, and consumer products. His vast expertise encompasses data analysis and modeling, designing robust data collection systems, and developing and implementing ML pipelines. As an accomplished researcher and educator, Sebastián consistently delivers captivating data-driven insights and user-friendly tools for technical and non-technical collaborators.
Implemented and executed an established media mix model for a newly formed geographic market and product portfolio, collaborating as an esteemed member of an MLOps team.
Conceptualized and executed the POC for a media mix model using Bayesian statistical modeling techniques, subsequently deploying it for optimal functionality.
Led a team of 5 ML engineers and data scientists in engineering, assessing, commercializing, and implementing an innovative media mix model for optimization purposes within the marketing department.
Designed, implemented, and deployed global marketing budget allocation across the organization's entire portfolio.
PythonMachine LearningSQLTensorflowDockerAmazon Web Services (AWS)
Bayesian Statistics
Machine Learning Operations (MLOps)
Statistical Modeling
Proof of Concept (POC)
Freelance
Data Scientist & ML Developer
2021 - Present (4 years)
Remote
Identifying valuable and quantifiable AI/ML opportunities for clients.
Translating business problems into technical designs and developing POCs.
Building teams and infrastructure needed to deploy scalable solutions into production.
Supporting existing tech teams on the R&D-heavy side of AI/ML, data science, and neurotech projects.
Verified and ensured the integrity of credit risk and accounting models within a prominent German financial institution.
Conducted predictive and prescriptive statistical analysis on soccer players' data, focusing on injury prediction and talent development within a respected Bundesliga team.
Implemented a robust data management system within an esteemed European banking institution.
Created MLOps pipelines for an in-house project, incorporating neural network architecture optimization techniques.
The text describes the deployment of a data management system used by a European bank for credit risk data.
Key responsibilities include setting up and deploying UAT/production environments and establishing a CI/CD pipeline for backend and frontend components.
The system utilizes data management for storage and examination of credit risk data.
