André Lopes

Online Resume

André Lopes

Data Scientist | Machine Learning Engineer | Software Engineering Student


Data Scientist at IBM’s Client Engineering team. Post-graduated in Data Science and Business Analytics at The University of Texas at Austin’s McCombs School of Business and currently pursuing a BSc. Software Engineering degree at UNINTER, where he is the founding Chapter Lead of its Google Developer Student Club (GDSC), recognized by Google as the largest students chapter world-wide in 2022. A former Submarine Pilot and Subsea Operations Supervisor, he has earned his associate degree in Electrical and Electronics Engineering from ETEP Faculdades and has studied Quality and Process Excellence at the University of Toronto.

Work Experiences

Data Scientist

IBM, Client Engineering | 2022 - Present
  • Acting as a key contributor to a pre-sales Client Engineering team, partnering with clients to understand business problems and propose Data and AI solutions
  • Contributing to co-creation of rapid proofs of concept and Minimal Viable Solutions that demonstrate business value, leading to client investment in strategic solutions
  • Translating business problems into leading-edge Analytics and Data Science solutions using consulting skills, industry expertise, and technical knowledge.
  • Familiar with Data Architecture and Engineering techniques to gather, prepare, cleanse, and transform client data for analysis and AI automation.

Machine Learning Engineer

IBM Consulting | 2021 - 2022
  • Working with the team responsible for building and maintaining the on-premises Analytics Platform for the Bank of Brazil, the biggest bank of Latin America in terms of IT infrastructure.
  • The Analytics Platform provides a JupyterLab or VS Code instance for each project with pre-installed libraries and kernels, orchestrated by Kubernetes and integrated with GitLab. It offers a complete DevOps pipeline for Machine Learning models, based on: GIT, Jenkins, Argo, Control-M, Papermill, Docker, Kubernetes and REST APIs.
  • Developing Exploratory Data Analysis (EDA) and Machine Learning models on a Small Data and Big Data environments by using the Hadoop HDFS, Apache Spark and PySpark, Hive, HBase, NiFi, YARN, Hue, IBM DB2, MongoDB.
  • Acting as Developer Advocate among the Data Science mentoring teams, sharing software engineering best practices, especially in Python, GIT operations, debugging code and helping by handling issues and improving code and teams’ performances.
  • Implementing LEAN/Six-sigma quality strategies and tools to keep the excellence in execution and high-quality standards in the services provided internally.

Google DSC Lead & Backend Developer

Google DSC | 2021 - Present

The Founding Lead of the globally recognized by Google in 2022 as the largest student chapter world-wide. "Google DSC Leads are leaders who believe that technology can do extraordinary things for the world." (Google)

As a Google DSC Lead, my main roles are:

  • Work with my university to start a student club. Select a core team and faculty advisor to support.
  • Host workshops to grow student knowledge on developer products and platforms through hands-on workshops and events.
  • Identify local partners to work with and lead project building activities.
  • Access to community management training and technical knowledge to help me be a stronger leader. Invitations to select Google events.
  • Access to a global network of student leaders, professional community organizers, industry experts, and Googlers to gain mentorship and share knowledge.

As Backend Developer I am in charge of:

  • Develop a web application (Django, Angular, PostgreSQL) to help small communities of agricultors and families to connect and support their non-profit CSA (Comunidade que Suporta a Agricultura, or Community that Supports Agriculture) organizations.

Subsea Robotics (ROV) Supervisor

Fugro | 2014 - 2021

ROVs (underwater Remotely Operated Vehicles) are basically submarine robots operated from a cockpit on an special vessel or oil rig, all programmed in C++, ROS 2 and Qt. I was not a developer of the ROV's softwares, but an Operations and Maintenance Supervisor, mainly performing inspections and interventions of subsea oilfield equipment. My main roles were:

  • Operation and Maintenance of the top-level ROV Submarine robots used on subsea inspections, construction and interventions;
  • Commissioning of multiple ROV systems, equipment from different manufacturers, using specific interfaces and communication protocols in order to centralize and interpret different returns on a main controller surface software;
  • Technical Support Team member for Fugro USA Marine, in Houston area, and Fugro Brazil working together with the Technical Managers; I have worked on, reviewed and created different procedures, forms, templates, work instructions and more; my greatest achievement was developing the Preventive Maintenance Manual to be implemented globally and some tools to automate most of our daily routines;
  • Coordination of new contracts, mobilization project designs, mobilization plans, tooling and devices specification in order to meet contract requirements, member of the investigation committee for ROV incidents, and an active contributor for the continuous improvement culture;
  • Developed a small project with Python and Pandas for automated analysis of data (CSV files) generated by the ROV software in order to increase efficiency of troubleshooting and our maintenance system.


Machine Learning Specialization


Machine Learning models with NumPy and Scikit-Learn, Neural Networks, Tree-based models, Clustering, Anomaly Detection, Recommender Systems, and Reinforcement Learning, by Andrew Ng.

Deep Learning Specialization


Deep Neural Networks, CNNs, RNNs, TensorFlow, architectures, optimization algorithms, tokenizers, and transformers, by Andrew Ng.

TensorFlow Developer Certificate


TensorFlow best practices and Convolutional Neural Networks for Computer Vision. RNNs, GRUs, and LSTMs for Natural Language Processing and Time Series Forecasting, by Andrew Ng and Laurence Moroney.

Fundamentals of Deep Learning


Mechanics of Deep Learning, Data Augmentation, Transfer Learning, Feature Extraction, TensorFlow, Keras.

Advanced Python

LinkedIn Learning

Standard Library, Object-Oriented Programming, Data Structures (Stacks, Queues, Deques, Linked Lists, Dictionaries), Algorithms, Decorators, and Essential Libraries.