Tech Portfolio

Pablo Reyes Martín

Machine Learning Engineer

Data Scientist and Engineer graduated at Universidad Carlos III (Madrid), with three years of experience in the Artificial Intelligence field. Currently located in the specialized unit of Artificial Intelligence of BBVA (BBVA AI Factory), working as a Machine Learning Engineer, technically supervising one of the bank’s Generative AI products. Previously I acquired knowledge mainly in Data Architecture, Big Data and Data Science both at work and educational level. With wide flexibility, to adapt to different branches of Artificial Intelligence as well as also to institutions in any field: medicine, biotechnology, genomics, sports, banking, energy, virtual reality, e-commerce, automotive, finance, transport, defense, home automation, etc. I am particularly interested in further developing my career in the artificial intelligence sector, specifically as a data scientist or machine learning engineer.

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Experience

Machine Learning Engineer
BBVA AI Factory (Boycor) March 2024 – Present
Building libraries on top of python frameworks, with the use of pattern designs mainly in Python, for a more secure and reusable code applying them to different processors of the bank (categorizer of Germany, Italy and Spain movements, detection of recurrences, identification of subscriptions). Use of pyspark, to process big data ETLs, optimizing runtime in pipelines and identifying bottlenecks with the use of the pyspark DAG to reduce costs of computation. Migrating streaming and batch python processes from an on-premise into the AWS ecosystem. Use of generative AI strategy to generate a financial program from different document reports in real time, reducing risk analysts workload, implementing a RAG architecture mounted in AWS cloud. Use of microservices (Docker), to mock AWS environment locally, and testing different AWS resources to deploy software safely. Working with SCRUM.
Big Data Engineer
Accenture February 2023 – March 2024
Focused on defining, implementing, and developing technical solutions based on analytics and data engineering problems, using computational architecture processes in Amazon Web Services. Working with different AWS resources of storage (S3, RDS, DocumentDB), computing (EMR, Lambda, EC2, Glue), monitoring (CloudWatch), orchestration (Datapipeline, Stepfunctions) and interaction (API Gateway, VPCs) of data, applied to energy business. Creation, support and management of optimized complex queries and ETLs based on distributed and parallel processing with pyspark, using structured and non-structured databases, as well as working with different format files (csv, parquet, avro). Use of best practices, working with SCRUM and CI/CD methodology.
Data and Research Scientist
Cognodata February 2022 – July 2022
Implementing solutions as a data scientist in the field of deep learning applied to medical and radiodiagnostic imaging to predict and interpret lung pathologies. Among other tasks, focusing on creating applications based on supervised machine learning and time series forecasting, including interpretability and explainability of models.
Data Analyst
Ayuntamiento de Madrid February 2022 – July 2022
Attendee as data scientist for the analysis and prediction of waste generated in the center of Madrid.

Education

Msc Technology School Big Data
Accenture February 2023 – April 2023
BSc Data Science and Engineering
Universidad Carlos III September 2018 – June 2022
Thesis based on a deep learning web ecosystem to diagnose pulmonary pathologies and assisting clinicians. Supervised by Prof Fernando Pozo Ocampo. Candidacy for honorific mention. GPA: 7.51/10
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HSc in Sciences
Instituto San Juan Bautista September 2016 – June 2018
GPA: 8.6/10
Middle School
Colegio Nuestra Señora del Buen Consejo September 2012 – May 2016
GPA: Honorific Mention

Tech Stack

Programming Languages

Python

RStudio

Java

Matlab

Web & UI

Streamlit

FastAPI

NodeJS

Dash

SparkUI

Android SDK

Big Data

Kafka

Hadoop

Spark

AI/ML Frameworks

Langchain

Pytorch

Tensorflow

Scikit-learn

Huggingface Transformers

Databases

MySQL

PostgreSQL

MongoDB

DynamoDB

Opensearch

Neo4J

Development Tools

VSCode

Docker

Podman

Linux

Terraform

Git

Jenkins

Cloud Computing

Google Cloud Platform

1 year of experience

Amazon web Services

more than 3 years of experience

Microsoft Azure

6 months of experience

Certificates

SOLID Principles

OpenWebinars ∙ September 2024

Course to design guidelines used to write maintainable, scalable, and flexible code by organizing software into more manageable parts.

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Get use of vectorial databases with Generative AI

DeepLearningAI ∙ July 2024

Course to build efficient, practical applications including hybrid and multilingual searches, for diverse industries, understand vector databases and use them to develop GenAI applications without needing to train or fine-tune an LLM yourself and learn to discern when best to apply a vector database to your application.

See certificate