Miguel Araujo
Verified Expert in Engineering
Machine Learning Developer
Miguel's background in software engineering and his PhD in Data Mining from Carnegie Mellon University make him the perfect bridge between product managers, developers, and data scientists. He has started and managed teams of data scientists and engineers to build data pipelines and machine learning infrastructure to support Insights and live ML deployments. He holds multiple best paper awards, and his transfer of research work to product features in fintech and ad tech has led to four patents.
Portfolio
Experience
Availability
Preferred Environment
Java, Scala, Python, Machine Learning, Data Mining, Architecture
The most amazing...
...software I've developed is a distributed machine learning algorithm for identifying the location where credit cards were stolen.
Work Experience
Principal Data Scientist
F5
- Redesigned Machine Learning Operations end-to-end flow.
- Migrated AI activities from legacy to a new cloud platform.
- Developed internal software to simplify fraud management across clients.
Director of Data Science
Semasio
- Built from scratch a team of data scientists and machine learning engineers to up to 5 individual contributors.
- Obtained €3M in EU funding to build Responsible AI products for the advertising industry.
- Responsible for the effectiveness and reach of our contextual targeting solution, doubling its monthly retained revenue in 6 months.
- Transferred research to the product and was involved in the necessary architectural decisions.
Assistant Professor
University of Porto
- Assistant Professor in the Computer Science department of the School of Science of the University of Porto.
- Responsible for the Introduction to Data Science course of the Data Science Master's degree.
- Responsible for the Data Structures course of the Bioinformatics and Computational Biology Master's degree.
Data Science Manager
Feedzai
- Worked with the Directors of Engineering and Product to break down and architect complex features and initiatives requiring cross-team collaboration that fed the roadmap of multiple teams.
- Drove technical discovery when analyzing new verticals and investment opportunities and was involved in due diligence of potential acquisition targets.
- Managed teams of 6-8 data scientists and data engineers developing the product. Ran discovery and developed prototypes in order to determine which concrete solutions should be integrated into the platform.
- Interfaced between Research and Product efforts and collaborated in multiple research projects and co-author 5 patents and multiple research papers.
Undergraduate Researcher
LIACC - Artificial Intelligence and Computer Science Laboratory
- Developed abstractions for real-time interaction with traffic simulators.
- Developed AI algorithms for the dynamic control of traffic lights in traffic simulators.
- Developed an API to allow code reuse of artificial intelligence solutions among multiple traffic simulators.
Education
Ph.D. Degree in Computer Science
Carnegie Mellon University - Pittsburgh, USA
Master's Degree in Informatics and Computing Engineering
University of Porto - Porto, Portugal
Skills
Libraries/APIs
Pandas, Scikit-learn, SQLAlchemy
Tools
IntelliJ IDEA, Git
Languages
Python, Scala, Java, PHP, HTML, CSS, JavaScript, SQL, C#
Frameworks
Apache Spark, Spark, Flask
Paradigms
Data Science, Functional Programming
Storage
PostgreSQL, Amazon S3 (AWS S3)
Platforms
Linux, Azure, Azure Synapse, Google Cloud Platform (GCP), Vertex AI, Docker, JVM
Other
Machine Learning, Data Mining, Algorithms, Recommendation Systems, Data Engineering, Big Data, Big Data Architecture, Data Analytics, Architecture, Software Engineering, Data Structures, Education, University Teaching, Containerization, GRAPH, Mining, Responsible AI
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