Carlos Guerreiro, Developer in Tuusula, Finland
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Carlos Guerreiro

Verified Expert  in Engineering

Bio

Carlos is an exceptional data generalist who brings vast experience in the design, implementation, and validation of data-intensive systems to all of his projects, along with deep expertise in machine learning and real-time stream processing. He has worked in the eCommerce and media industries, working for large corporations and startups. Carlos is a versatile engineer and looks forward to his next challenge.

Portfolio

Freelance Clients
Redis, C++, Node.js, JavaScript, R, Python, Machine Learning, Amazon Kinesis...
MarkaVIP
Oracle, MySQL, Redshift, Amazon Kinesis, C++, Java, R, Python, Optimization...
Codento's clients
Ruby on Rails (RoR), Java, CoffeeScript, Node.js, JavaScript, Python, Scala...

Experience

  • C++ - 20 years
  • Python - 13 years
  • Machine Learning - 10 years
  • NumPy - 8 years
  • Pandas - 7 years
  • Scala - 5 years
  • Apache Spark - 5 years
  • TensorFlow - 3 years

Availability

Part-time

Preferred Environment

Apache Spark, Amazon Web Services (AWS), Python, Scala, Machine Learning, TensorFlow, PyMC, Apache Kafka

The most amazing...

...thing I've built is a low latency custom recommendation system for an eCommerce startup doing flash sales.

Work Experience

Freelance Data Scientist and Engineer

2010 - PRESENT
Freelance Clients
  • Built an end-to-end Python NLP pipeline for a cybersecurity firm, from text extraction to knowledge recognition, using fine-tuned open-source LLM/ Hugging Face on AWS. Also, a pipeline to parse and categorize custom search strings for visualization.
  • Created an end-to-end Python NLP pipeline for a fintech startup, from text extraction to user interaction, using fine-tuned and adapted open-source LLM and Hugging Face on GCP.
  • Designed and built various machine learning models for risk assessment, customer churn, and rate optimization for a retail bank using Python, Pandas, NumPy, SciPy, PyMC, TensorFlow, and scikit-learn. Deployed with custom FastAPI back end.
  • Designed and built a custom system for products offering recommendations from transactions and demographic data (retail bank) using Python, Pandas, NumPy, and C++. Deployed with custom FastAPI back end.
  • Designed and built a continuous analytics backbone and a data warehouse in a hybrid onsite/AWS environment with Kafka, Scala, Python, and Redshift.
  • Designed and built a real-time data fusion pipeline to create a complete picture of customer transactions from different systems.
  • Assembled a low-latency custom recommender system for eCommerce flash sales using Python and C++ for an eCommerce startup. Deployed with custom C++/Boost.Asio back end.
  • Built a bespoke transaction risk analysis system for eCommerce using Python and R.
  • Refactored, optimized, fixed, streamlined, documented, and further developed a complex and largely undocumented Airflow delivery workflow.
  • Ported to Scala, optimized, tested, and documented Spark UDF/UDAF/UDTs written in Java and included functions dealing with text and URL matching, information extraction from text and URLs, and supporting data structures. Wrote Python bindings.
Technologies: Redis, C++, Node.js, JavaScript, R, Python, Machine Learning, Amazon Kinesis, Amazon Elastic MapReduce (EMR), AWS IAM, AWS ELB, AWS CLI, Redshift, Amazon Redshift Spectrum, Amazon Athena, Spark SQL, Spark ML, Apache Spark, FastAPI, Flask, Apache Airflow, TensorFlow, Keras, PyTorch, Pandas, SciPy, NumPy, PyMC, GitHub, GitHub API, Docker, MLflow, Prometheus, Grafana, Apache Kafka, Confluence, Scala, Deep Learning, Elasticsearch, SQL, Delta Lake, PySpark, Bayesian Statistics, Statistics, PostgreSQL, C, D3.js, Optimization, Mixed-integer Linear Programming, PuLP, RocksDB, Recommendation Systems, Distributed Computing, Natural Language Processing (NLP), Jupyter Notebook, Hadoop, Git, Eigen, Scikit-learn, StatsModels, Data Science, Data Engineering, Theano, Seaborn, Matplotlib, ETL, Linux, Scripting, Data Extraction, Beautiful Soup, Command-line Interface (CLI), DevOps, Kubernetes, Data Architecture, Database Architecture, Architecture, Back-end, SaaS, GeoPandas, Shapely, Algorithms, Microservices, RESTful Microservices, REST APIs, Pytest, Amazon S3 (AWS S3), Boost.Asio, Google Cloud Platform (GCP), Hugging Face, Llama 2, LangChain, Beautiful Soup 4, Selenium, FAISS, Abstract Syntax Trees (AST), pylint, Unit Testing, Databricks, SQLAlchemy, Pydantic, ChatGPT

Director of Data Science

2015 - 2016
MarkaVIP
  • Implemented real-time analytics on operations, modeled interventions on customer experience to address returns and cancellations, built a policy optimizer through retrospective simulation with historical data, and enabled it as a microservice.
  • Expanded the policy optimizer to improve order profitability by optimizing basket constraints and incentives.
  • Implemented various improvements to the product recommender, including the use of fine-grained recorded impressions as a negative signal and more flexibility in handling catalog metadata.
  • Built and deployed a foundational analytical backbone for the company in AWS with Kinesis, Redshift, and Spark.
  • Integrated continuous data ingestion from key systems into the analytical backbone, whenever practical, through low latency interfaces such as database replication.
  • Migrated some interaction tracking systems to the backbone and the recommender.
  • Conducted retrospective sourcing performance and pricing analysis by replaying row mutations continuously captured from database replication logs and stored in Redshift (Python/C++).
Technologies: Oracle, MySQL, Redshift, Amazon Kinesis, C++, Java, R, Python, Optimization, D3.js, Machine Learning, Statistics, Bayesian Statistics, Recommendation Systems, Apache Spark, Git, Data Science, Data Engineering, ETL, Linux, Microservices, RESTful Microservices, REST APIs, Amazon S3 (AWS S3), Pytest, pylint, Unit Testing

Software and Data Architect

2011 - 2015
Codento's clients
  • Built an image upload/pre-processing pipeline for a media startup using Node.js and MongoDB on AWS. Included single sign-on with a Ruby on Rails app in the back end.
  • Created custom, interactive data displays for a bespoke structured messaging application using D3.js. Implemented real-time updates.
  • Implemented a structured messaging application. Contributed to the Python/Django back-end and the CoffeeScript front end.
  • Built a custom C# distributed data analysis pipeline to perform MATLAB jobs on AWS.
  • Designed and implemented a custom interactive data analysis and visualization for economic data along with a Python back-end and D3.js visualization.
  • Assembled a custom nurse schedule and route optimization system for a healthcare software startup. Worked on pre-processing and mixed integer model formulation for Gurobi with Python/Pandas/NumPy/PuLP, D3.js visualization of solutions, and Flask API.
  • Modernized the system design and implementation of a Java/Spring back end for real-time transport logistics. Improved scalability and performance.
  • Designed and implemented a reference application for a high-security network architecture for a banking customer with Scala/Play, Slick, and two-factor authentication.
  • Contributed to a large-scale online storage system implementation using Python and PostgreSQL. Contributed to embedded security appliances in C.
  • Developed a custom MATLAB system to tune a legacy application from data during black-box optimization (derivative-free).
Technologies: Ruby on Rails (RoR), Java, CoffeeScript, Node.js, JavaScript, Python, Scala, Slick, MongoDB, PostgreSQL, D3.js, AWS CLI, C, Gurobi, PuLP, Optimization, Mixed-integer Linear Programming, Front-end, CSS, HTML, Flask, Bottle.py, CVXOPT, Git, MATLAB, Data Science, Data Engineering, Tornado, Linux, C#, .NET, Data Architecture, Architecture, SaaS, Microservices, RESTful Microservices, REST APIs, Spring, Amazon S3 (AWS S3), Pytest, pylint, Abstract Syntax Trees (AST), Unit Testing

Chief Software Architect

2009 - 2010
Nokia
  • Prototyped a voice- and gesture-based user interface for in-car mobile phone usage at various levels of fidelity ranging from Wizard of Oz to software proof-of-concept (Python, Java, Sphinx).
  • Defined software architecture for a family of in-car products, with input to hardware platform selection.
  • Planned costs, schedule, and execution of multiple new product development scenarios.
  • Organized and moderated usability studies for prototype validation and iteration.
  • Conducted rigorous feasibility studies and software architecture reviews at Gear.
Technologies: Java, Python, Software Architecture, Bluetooth, Planning, Usability, Usability Testing, Speech Recognition, Architecture, Technical Leadership, Leadership, Unit Testing

Senior R&D Manager

2003 - 2009
Nokia
  • Recruited and ramped up the Maemo application framework team from scratch.
  • Defined the application framework architecture and development strategy.
  • Led the implementation of three major software generations along with updates.
  • Impacted Nokia's entry into open-source development.
  • Developed a considerable subcontracting and partnering network for Linux development.
  • Contributed to the initial product concept definition.
Technologies: IT Project Management, Agile Project Management, Software Architecture, Open Source, Due Diligence, Recruitment, Leadership

Senior Software Engineer

2001 - 2003
Nokia
  • Prototyped a small-footprint relational database for small Linux devices in C++ for the Nokia Research Center.
  • Prototyped a personal information manager for handheld devices based on semantic web technology in Python.
  • Studied and evaluated architectural options for an application framework aimed at Linux-based handheld devices adopted by the nascent Maemo project.
Technologies: Python, C, C++, Databases, Embedded Linux, Semantic Web, RDF, Software Architecture, Graphical User Interface (GUI), GNOME, Qt, GTK+, ANTLR

GIS/Computer Graphics Freelancer

1998 - 2001
Freelancer clients
  • Built a geographic information system (GIS) to edit the land cadaster for the Portuguese Ministry of Agriculture using C++, Windows, and Oracle technologies.
  • Constructed a custom C++ framework for real-time manipulation of topologically integrated geographic vector data.
  • Assembled a geographical decision support system for semi-automated execution and optimization of land-consolidation projects for specialized consultancy using C++.
  • Developed, licensed, and finally sold a ray-tracing rendering module for use with interior design software written in C++.
  • Shaped GIS to edit an olive tree cadaster for the Portuguese Ministry of Agriculture, with integrated olive tree recognition from aerial photography, built with C++ in Windows.
  • Designed and implemented flooring tiling algorithms for 3D interior design software.
Technologies: Oracle, Python, C++, Computational Geometry, Computer Graphics, GIS, Optimization, Unit Testing

RawHash

https://github.com/pconstr/rawhash
An experimental, binary-friendly alternative to using a hash as a key value cache, in C++, for Node.js.

Keys are binary buffer objects rather than strings. Values are arbitrary objects.

RawHash is built on Google SparseHash and MurmurHash3.

Rdb-parser

https://github.com/pconstr/rdb-parser
An asynchronous streaming parser for Redis RDB database dumps, written in 100% JavaScript, intended for use in Node.js, and released as open-source. It's useful for diagnostics, data conversion, or even as part of a data processing pipeline.

Incremental Random Forest

https://github.com/pconstr/irf
An implementation in C++, with Node.js and Python bindings, of a variant of Leo Breiman's random forests.

The forest is maintained incrementally as samples are added or removed - rather than fully rebuilt from scratch every time to save resources.

It is not a streaming implementation, as all the samples are stored and will be re-seen when required to recursively rebuild invalidated subtrees. The effort to update each tree can vary substantially, but the overall effort to update the forest is averaged across the trees and tends not to vary significantly.

Data-Graft.js

https://github.com/pconstr/data-graft.js
An animation-friendly, differential document object model (DOM) template engine that is self-contained and framework-agnostic. Built to experiment with dynamic data/DOM binding, focusing on flexibility for animating data-change transitions.
1991 - 1996

Master's Degree in Computer Science

Universidade Nova de Lisboa - Lisbon, Portugal

Libraries/APIs

Pandas, Node.js, NumPy, Matplotlib, Bottle.py, Eigen, Scikit-learn, SciPy, Theano, D3.js, TensorFlow, Keras, PyMC, PySpark, REST APIs, SQLAlchemy, Pydantic, Spark ML, PyTorch, GitHub API, Slick, Beautiful Soup, Shapely, Beautiful Soup 4

Tools

Git, Amazon Redshift Spectrum, Spark SQL, Apache Airflow, GitHub, StatsModels, Seaborn, Pytest, pylint, MATLAB, Amazon Elastic MapReduce (EMR), AWS IAM, AWS ELB, AWS CLI, Amazon Athena, Grafana, Confluence, Gurobi, GNOME, GTK+, GIS, ANTLR, ChatGPT

Languages

Python, C++, C, Java, SQL, R, Scala, HTML, CoffeeScript, JavaScript, CSS, RDF, Prolog, C#

Paradigms

Unit Testing, Distributed Computing, Parallel Computing, Distributed Programming, ETL, Microservices, Functional Programming, Usability Testing, Agile Project Management, DevOps

Platforms

Linux, Amazon Web Services (AWS), Docker, Apache Kafka, Jupyter Notebook, Databricks, Oracle, Embedded Linux, Kubernetes, Google Cloud Platform (GCP)

Storage

Redis, Redshift, MongoDB, PostgreSQL, Databases, Database Architecture, Amazon S3 (AWS S3), MySQL, RocksDB, Elasticsearch

Frameworks

Apache Spark, Hadoop, Flask, Ruby on Rails (RoR), Django, Qt, .NET, Spring, Selenium

Other

Machine Learning, Data Science, Amazon Kinesis, Software Engineering, Mathematics, FastAPI, Deep Learning, Bayesian Statistics, PuLP, Optimization, Recommendation Systems, Software Architecture, IT Project Management, Open Source, Random Forests, Data Engineering, Scripting, Data Extraction, Command-line Interface (CLI), Data Architecture, Architecture, Technical Leadership, Back-end, Leadership, SaaS, Algorithms, Abstract Syntax Trees (AST), Natural Language Processing (NLP), Tornado, MLflow, Prometheus, Delta Lake, Statistics, Mixed-integer Linear Programming, Front-end, CVXOPT, Bluetooth, Planning, Usability, Speech Recognition, Due Diligence, Recruitment, Semantic Web, Graphical User Interface (GUI), Computational Geometry, Computer Graphics, DOM, GeoPandas, RESTful Microservices, Boost.Asio, Hugging Face, Llama 2, LangChain, FAISS

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