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Matheus – Python, Deep Learning, Big Data, experts in Lemon.io

Matheus

From Brazil (UTC-3)

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Data ScientistSenior
Machine Learning Engineer
8 years of commercial experience
AI
Analytics
Consumer goods
Data analytics
Insurance
Logistics
Machine learning
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Matheus – Python, Deep Learning, Big Data

Matheus is a business-oriented Senior Data Scientist with extensive experience in forecasting, analytics, and pricing models. He possesses strong communication skills, demonstrating the ability to convey ideas clearly. Matheus also has a great understanding of machine learning principles and exhibits clear thinking in problem-solving scenarios. Moreover, his prior experience includes making architectural decisions and managing people, making Matheus a great addition to any team.

Main technologies
Python
5 years
Deep Learning
4 years
Big Data
5 years
Data Science
6 years
Tensorflow
3.5 years
SQL
7 years
Machine learning
6 years
Additional skills
Matplotlib
Pandas
NumPy
PyTorch
API
Apache Hadoop
Apache Airflow
BigQuery
Containers
Bash
Docker
AWS SageMaker
GCP
GCP Compute Engine
Kubernetes
Vertex AI
Databricks
Web scraping
Polars
FastAPI
Pydantic
RAG
MLOps
LangChain
PostgreSQL
Direct hire
Potentially possible
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Experience Highlights

Senior Data Scientist
Dec 2023 - Ongoing1 year 5 months
Project Overview

Working as a Senior Data Scientist/Machine Learning Engineer in the airline industry sector. Matheus led end-to-end development and API deployment, as well as best practices and templates.

Responsibilities:
  • Set up DS and MLops guidelines and infrastructure;
  • Created models to compute the causal impact of price changes and the probability of a work order getting pushed;
  • Created data quality and monitoring frameworks;
  • Added an LLM classification step to clean up text data related to work orders.
Project Tech stack:
Databricks
Microsoft Azure
Lead Data Scientist
Dec 2021 - Dec 20232 years
Project Overview

The cutting-edge forecasting model is designed to predict sales unit forecasts for new products across diverse industries and countries. By integrating state-of-the-art machine learning models and adhering to MLOps best practices, it ensures precision and reliability in predictions.

Responsibilities:
  • Led the technical architecture, development, and implementation of the model pipeline to guarantee its efficiency, reliability, and scalability;
  • Directly managed a team member responsible for executing various tasks within the model pipeline, offering guidance, support, and mentorship as necessary;
  • Coordinated the integration of our model pipeline with multiple clients, ensuring seamless interaction and alignment with their systems and requirements;
  • Committed to achieving low forecasting error rates by consistently refining and optimizing the model pipeline through thorough testing, validation, and performance monitoring.
Project Tech stack:
Python
Machine learning
Docker
Kubernetes
GCP Compute Engine
Data Science
FastAPI
Polars
Pandas
Tensorflow
PyTorch
Senior Data Scientist
Jun 2020 - Nov 20205 months
Project Overview

This project was focused on providing segment pricing for insurance of theft and damage of mobile phones. Based on the user's personal information and history, the pricing in the model is adjusted.

Responsibilities:
  • Spearheaded the model's achievement of a 30% reduction in average premiums while maintaining the same risk level;
  • Implemented the pricing model using Tweedie regression;
  • Utilized Docker and API integration for model deployment;
  • Oversaw model performance monitoring;
  • Orchestrated project development;
  • Ensured alignment with business stakeholders.
Project Tech stack:
Python
Machine learning
Data Science
API
Data Science Specialist
Jul 2020 - Nov 20203 months
Project Overview

Machine learning model tailored to assess insurance claims for automatic approval based on historical data. This innovative model drastically reduced claim payment processing time from a potential maximum of 14 days to a mere 2 hours. Also, it successfully automated the payment of 30% of claims, resulting in significant savings in human analysis time. In essence, the model revolutionized the efficiency and speed of claim processing while enhancing cost-effectiveness through automation.

Responsibilities:
  • Developed the model for claims evaluation, ensuring accuracy and efficiency in decision-making processes;
  • Created comprehensive unit tests to validate the functionality and reliability of the model;
  • Deployed the model for claims evaluation via API integration and Docker containerization, ensuring seamless integration;
  • Implemented monitoring mechanisms to assess the model's performance in evaluating claims;
  • Managed the project lifecycle, including planning, execution, and monitoring of tasks and milestones;
  • Collaborated closely with business stakeholders to understand requirements and ensured alignment between model development efforts and business objectives.
Project Tech stack:
Python
Machine learning
Data Science
Senior Data Scientist
Jul 2019 - Sep 20191 month
Project Overview

This is an intent recognition model based on WhatsApp chat for detecting customer friction.

Responsibilities:
  • Developed and deployed machine learning models;
  • Monitored model performance;
  • Oversaw model project management.
Project Tech stack:
Python
Data Science
Machine learning

Education

2018
Statistics
Master Degree
2024
Artificial Intelligence
Phd

Languages

English
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