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About

José A. Perdiguero López

[email protected]

Málaga, Spain

As a dedicated computer scientist, my fervor for technology and innovation has been unwavering. Continuously seeking fresh challenges, I possess an insatiable thirst for knowledge and growth. My expertise lies in crafting cutting-edge artificial intelligence, machine learning, and data science architectures and solutions, emphasizing resilience and scalability as paramount. With a relentless commitment to pushing boundaries, I am poised to tackle complex problems and drive transformative outcomes in the digital landscape.

Experience

Industry

  • Vortico

    Co-Founder

    Málaga, Spain

    Jan 2022 - Present

    Helping businesses enhance and expand their AI and technology capabilities.

  • Tenth Revolution Group

    Senior Data Architect

    London, United Kingdom

    Sep 2023 - Present

    In my current role at Tenth Revolution Group, I serve as an Independent Consultant, specializing in Software Architecture and Development projects with a strong emphasis on Machine Learning and Data Engineering. Leveraging my expertise, I provide strategic guidance and technical leadership in designing and implementing innovative solutions tailored to the unique needs of diverse projects.

    My responsibilities encompass a spectrum of tasks, including but not limited to architectural design, code development, and the integration of machine learning principles into software projects. Through this role, I contribute to the successful execution of projects, ensuring they align with industry best practices and standards.

  • Adevinta

    Machine Learning Enabler

    Barcelona, Spain

    Oct 2022 - Dec 2023

    In my capacity as a Machine Learning Enabler at Adevinta, Europe, I have been at the forefront of steering the company's strategic shift towards full AI adoption. My responsibilities include the implementation of industry standards for Machine Learning Operations (MLOps). I have led the development of template repositories and systematized machine learning workflows, leveraging cutting-edge technologies such as Kubeflow and adhering to MLOps standards.

    Beyond MLOps, I have played a crucial role in ML Enabling by delivering recurring talks and live coding sessions. These efforts have been instrumental in leading and educating the team on ML engineering practices. Additionally, I have designed a standardized route for machine learning across various verticals of the company, with a primary focus on streamlining and guiding the implementation of ML solutions.

    As a leader in Data Engineering through my ML Enabler role, I have overseen data engineering efforts involving data ingestion into Redshift and S3. This also includes data transformation using Spark and Databricks, ensuring a robust data foundation to support the company's machine learning initiatives.

  • Stratyfy

    Machine Learning Consultant

    New York, United States

    Jul 2022 - Nov 2022

    During my tenure as a Machine Learning Consultant at Stratyfy, New York, USA, I assumed a leadership role in building and productionalizing machine learning models, specifically for credit-card fraud detection. This encompassed not only the development of models but also ensuring their readiness for deployment in real-world scenarios.

    In addition to my responsibilities in machine learning, I took the lead in the design and implementation of a Data Lake dedicated to credit-card transactions. This signifies my leadership in establishing a robust data foundation essential for the success of machine learning applications.

  • Covalto

    Senior Data Architect

    Ciudad de México, México

    Jun 2020 - Jul 2022

    In the role of Senior Data Architect at Covalto, I assumed a critical position in the organization, overseeing the design, leadership, and execution of the entire data solution life cycle. My responsibilities encompassed the strategic development of a comprehensive data solution, strategically addressing the ingestion of data from diverse sources. This involved orchestrating meticulous processes for gathering and curating data, ensuring a standard of quality and reliability.

    Another pivotal aspect of my role involved leading the creation of a machine learning-driven segment, dedicated to generating new data. Leveraging advanced machine learning techniques, I played a crucial role in fostering innovation within the data ecosystem and staying abreast of cutting-edge technological advancements.

    Furthermore, I spearheaded the establishment of a robust final stage, focusing on the production of valuable reports and the creation of queryable sources. Close collaboration with product-oriented teams was paramount to tailor outputs that met their specific needs, seamlessly integrating into the overall product development cycle.

    My skill set, encompassing Data Streaming, Data Architecture, Serverless, Data Science, Machine Learning, and Data Engineering, played a vital role in architecting a scalable and efficient solution. Throughout my tenure at Covalto, I ensured the alignment of the data architecture with organizational goals, contributing significantly to the company's overall success and product development strategy.

  • Piksel

    Software Architect

    York, United Kingdom

    Jun 2019 - Jun 2020

    In my role as a Software Architect at Piksel Inc, I led, designed, and developed projects related to media metadata within a product-oriented context. Managing a highly-skilled team, we were end-to-end responsible for a suite of services designed for the gathering, enrichment, and exposure of various types of media metadata.

    These services, built using modern technology stacks and designed with Big Data and Artificial Intelligence techniques, formed the backbone of a data-driven and polyglot architecture. Mainly employing Python, Java, and JavaScript languages, alongside multiple relational and NoSQL databases, the architecture included highly-scalable serverless services based on streaming engines such as Kafka and AWS Kinesis.

  • Whalar

    Head of Data Science

    London, United Kingdom

    Jun 2018 - Jun 2019

    As the Head of Data Science at Whalar, I held a position of responsibility over the entire data ecosystem within the company. The primary objective of this ecosystem was to provide a reliable and continually updated source of metadata from influencers. This data was enriched with various own- generated metadata, incorporating fraud detectors, followers health evaluators, segmented potential exposition, and more, employing diverse Machine Learning techniques.

    A secondary goal involved using the data ecosystem as a Business Intelligence platform to enhance the sales process and integrate feedback from sales campaigns into our data system. The entire system was built following a Kappa architecture, utilizing Kafka streams, modern APIs based on REST or GraphQL, and Data Warehousing to achieve significant efficiency gains.

  • Piksel

    Lead Developer

    York, United Kingdom

    Jul 2016 - May 2018

    During my tenure as a Lead Developer at Piksel Inc, I collaborated within a dynamic team to build an ecosystem of services based on Artificial Intelligence. Leveraging Python and various frameworks, including Django, Celery, Scrapy, TensorFlow, and Gensim, we addressed multiple challenges in image and video processing, as well as natural language processing for text patterns recognition.

    Every service was intricately built on top of the latest infrastructure using AWS services, with containerization through Docker and Mesos/Marathon. Continuous integration and continuous deployment principles were applied using Gitlab and GoCD pipelines.

  • Ebury

    Lead Big Data Engineer

    London, United Kingdom

    Apr 2015 - Jul 2016

    As the Lead Big Data Engineer at Ebury, my primary focus was within the Business Intelligence domain. I played a pivotal role in architecting, designing, and developing Big Data solutions aimed at enhancing the sales process, campaigns, and feedback mechanisms. I utilized various Weak Artificial Intelligence techniques, including Fuzzy Logic Systems and Artificial Neural Networks, applying Machine Learning methodologies to achieve optimal results.

  • Ebury

    Web Backend Engineer

    London, United Kingdom

    Jul 2014 - Jul 2016

    In my capacity as a Web Backend Engineer at Ebury I was an integral part of a team responsible for monitoring and improving service performance. This involved developing tools for system health, refactoring significant components of applications, and implementing technologies such as cache layers and clustering to databases.

    One of the key aspects of this role was the design and implementation of a performance test suite, crucial for effective benchmarking of our applications. My responsibilities extended to understanding the entirety of the system, constant monitoring, and the continuous development of tools to ensure the health and efficiency of our services.

Academic

  • Research scholarship

    Universidad de Málaga

    Málaga, Spain

    Sep 2012 - Mar 2014

    During my time as a Research Scholar at the Universidad de Málaga, I conducted research on Algorithmic Musical Composition and Music Information Retrieval, focusing on Fuzzy Logic systems.

Education

  • BEng.+MEng. Computer Science

    Universidad de Málaga

    Málaga, Spain

    Jun 2013

Research

Talks and seminars

  • Flama: Framework for Lightweight Applications and Machine learning Automation

    OpenSouthCode

    Málaga, Spain

    Jun 2023

  • Machine Learning services validation

    Test Academy

    Madrid, Spain

    Sep 2019

  • High-performant asynchronous APIs

    PyCon

    Alicante, Spain

    Sep 2019

  • New generation of APIs

    PyCon

    Málaga, Spain

    Oct 2018

  • Create, package and distribute your own Python application

    PyCon

    Cáceres, Spain

    Sep 2017

  • Flex schemas with PostgreSQL and Django

    OpenSouthCode

    Málaga, Spain

    May 2017