Passion Fuels Purpose! 

Biography

With 4+ years of experience in data engineering and data science, including roles at Intel Corporation and various startups, I specialize in transforming data into actionable insights. I have led the development of +600GB data lakes and data warehouses, built forecasting models to reduce churn for a 6 million-user cybersecurity app, and developed performance dashboards for +50 AI workloads running on Intel's GPUs.

My work encompasses building machine learning models, developing real-time data architectures, and optimizing data processes to drive impactful outcomes. With Master's degrees from the University of Southern California and Ecole Centrale Paris, I thrive in dynamic environments and am dedicated to delivering innovative data solutions.

Daniel
+

years of experience

+

projects completed

+

technologies & tools

Skills

DE/DS
Python
SQL
NoSQL
ReactJS
AWS
Terraform
Airflow
TypeScript
Databricks
PowerBI
PyTorch
LLMs
Data Lake
JavaScript
Data Warehouse
Spark

Experience

  • ML Engineer @Rose AI

    Jun 2024-Present | Los Angeles, CA

    Fine-tune LLM agent to enhance chart generation capabilities on Rose AI, offering financial analysts a robust data solution experience. Developed a cost analysis platform to estimate the costs of 5 AI agents based on GPT-4o.

  • Data Analyst @Intel Corporation

    May 2023-May 2024 | Los Angeles, CA

    Developed a comprehensive PowerBI dashboard to detect performance deviations in 50+ AI workloads on Ponte Vecchio GPUs and created a RAG application using LLMs to integrate customer engagement updates from various sources into PowerBI reports.

  • Data Engineer @Akad Seguros

    Jan 2022-Feb 2023 | Rio de Janeiro, BR

    Orchestrated the design of a 600GB Data Lake and 50GB Data Warehouse on AWS, integrating over 100GB of data from eight sources using S3, Glue, Lambda, and Step Functions. The project, which was published on the AWS Blog, involved creating a multi-layered architecture with data ingestion via DMS, transformation using EMR and Spark, and solving synchronization challenges with CDC and Databricks (Delta Lake).

  • Data Scientist @Cyberlabs

    Jul 2019-Dec 2021 | Rio de Janeiro, BR

    Spearheaded a team of 3 in constructing a system aiding 20+ companies in controlling COVID-19 spread for 3,000 employees; implemented event-driven serverless architecture on AWS employing Infrastructure as Code (Terraform) and Lambda, RDS and API Gateway. Utilized Amazon QuickSight to present data to over 30 different clients

  • Software Engineer @SoftBank Robotics

    Jun 2018-Dec 2018 | Paris, FR

    Developed a C/C++ firmware module for a robot's inductive sensor (LDC1312/4) and presented an analysis to the firmware team, validating the sensor's performance against two key KPIs.

Education

  • Master of Science in Applied Data Science

    2022-2024 | University of Southern California (USC)
    Los Angeles, CA

    Awarded the Dean's Master's Scholarship - Top 1%
    Relevant courses include Data Mining, Probability, Statistics and Natural Language Processing.

  • Master of Science in Engineering

    2016-2019 | École Centrale Paris
    Paris, France

    Awarded the Eiffel Excellence Scholarship
    Relevant courses include Stochastic Modeling Theory of Queues, Software Development and Statistics.

  • Bachelor in Control and Automation Engineering,
    Minor in Mathematics

    2014-2019 | Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
    Rio de Janeiro, Brazil

    Awarded the Merit-Based Scholarship
    Relevant courses include Artificial Intelligence, Signal and Systems and Digital Signal Processing.

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