Matheus Mori / AI ENGINEERING · DATA SCIENCE

AI Engineer
& Data Scientist

Building production-oriented AI, machine learning and data products.

I work across data, machine learning and AI — turning complex problems into systems people can actually use.

Explore my work Resume

01 / ABOUT

I build at the intersection of
data, machine learning and AI.

BACKGROUND

  • Statistics
  • Data Science
  • Machine Learning
  • Analytics

CURRENT DIRECTION

  • AI Engineering
  • Applied AI
  • Production ML

I'm a statistician and data professional focused on turning analytical problems into reliable products and systems.

My background spans analytics, machine learning, experimentation and decision-support products. Today, I'm increasingly focused on AI engineering — especially systems that combine LLMs, retrieval, agents, evaluation, APIs and production-oriented software practices.

DATA SCIENCE

Statistical modeling, experimentation, forecasting and machine learning.

AI ENGINEERING

LLM applications, RAG, agents, evaluation and AI systems.

DATA PRODUCTS

Turning models and analysis into tools people can actually use.

02 / SELECTED WORK

Systems designed to
solve real problems.

A selection of AI systems, machine learning systems and data products.

01 / AI ENGINEERING · AGENT ORCHESTRATION

DataLab OS

A local-first, observable Data Science agent system built with LangGraph, covering profiling, EDA, modeling and independent methodological review.

Python · LangGraph · FastAPI · Next.js · React Flow

GitHub
orchestration
LANGGRAPHorchestration
backend tests
118backend tests
frontend tests
97frontend tests
independent gate
REVIEWindependent gate

02 / MACHINE LEARNING · DATA PRODUCT

Procurement Intelligence

A spend and price intelligence platform built on 5.7M+ public procurement transactions.

Python · DuckDB · LightGBM · Streamlit

GitHub Live Demo
transactions
5.7M+transactions
automated tests
124automated tests
ML validation
TEMPORALML validation
dashboard
LIVEdashboard

03 / MACHINE LEARNING · PEOPLE ANALYTICS

Employee Attrition Prediction

An interpretable classification workflow focused on identifying employees at higher attrition risk.

Python · Scikit-learn · Imbalanced-learn

GitHub
recall
74%recall
class balancing
SMOTEclass balancing
optimization
THRESHOLDoptimization
cross-validation
5-FOLDcross-validation

03 / CASE STUDIES

The reasoning behind
the work.

Problems, architecture, methodology, trade-offs and evidence behind selected work.

01 / DATA ENGINEERING · ECONOMIC INTELLIGENCE

Steel Indicator

Building an auditable economic indicator from fragmented public data.

PROBLEM
Fragmented public sources and changing policy parameters.
ENGINEERING
Immutable vintages and source provenance.
METHODOLOGY
Versioned index methodology and declared proxies.
RELIABILITY
529 automated tests.
GitHub

02 / APPLIED RESEARCH · DATA SCIENCE

Developer Market Research

Research and data analysis developed during my time at Rocketseat, with findings on women's representation in technology reaching CNN Brasil.

QUESTION
What does the Brazilian technology workforce look like?
RESEARCH
Market and workforce data analysis, conducted during my time at Rocketseat.
FINDING
Women represented a minority of technology employment in the reported analysis.
IMPACT
The finding reached CNN Brasil coverage.
Watch coverage

04 / EXPERIENCE

Where I've worked
and what I've built.

Professional experience across finance, consulting and technology — applying analytics, machine learning, experimentation and data products to real business problems.

Resume

  1. Banco BV

    2025 — 2026

    People Analytics Analyst Pleno · Data Analytics

    Built and evolved analytics, forecasting and decision-support products covering a workforce of 4,000+ employees and serving multiple levels of leadership. Worked across SQL Server, Power BI, Python and Databricks.

    SQL Server · Power BI · Python · Databricks

  2. BIP Consulting

    2024 — 2025

    People Analytics · Data Analytics

    Took ownership of People Analytics operations and redesigned monthly international reporting, reducing consolidation from about one week to one day. Built ETL and automation flows with Power Automate, Python and Power Query.

    Python · Power Query · Power Automate · ETL

  3. Contmatic Phoenix

    2022 — 2023

    Data Science Junior · Growth & Marketing Analytics

    Worked across experimentation, segmentation, churn/LTV, funnels and campaign analytics on a base of ~1M leads and ~60k users. A series of data-driven optimizations contributed to ~11% higher conversion and ~20% lower CAC.

    Python · SQL · Experimentation · Growth Analytics

  4. Rocketseat

    2021 — 2022

    Data Science Junior · Growth & Customer Analytics

    Applied data science to segmentation, retention, cohorts and growth analytics across 60k+ paying students. A decision-tree segmentation initiative contributed to ~15% higher course-purchase conversion.

    Python · R · SQL · Customer Analytics

05 / RESEARCH & RECOGNITION

Research and milestones
that shaped my work.

Academic investigations and early projects across statistics, forecasting and applied data science.

  1. RESEARCH / 01

    Wavelet Multivariate Time Series Analysis

    UFSCar · Undergraduate Thesis · 2023

    Undergraduate statistics research examining how relationships among financial markets change across time and scale using wavelet methods.

    Time Series · Statistics · Wavelets

    View research

  2. RECOGNITION / 01

    FarmIA — Santander Data Challenge

    1st Place · 2020

    First-place data challenge project developed by a five-person team, using statistical modeling and agrometeorological data to support agricultural planning.

    1ST PLACE · 100+ TEAMS

    Applied Data Science · Agriculture

    GitHub

  3. RESEARCH / 02

    Retail Sales Forecasting

    Digital House · Final Data Science Project

    Academic forecasting project exploring monthly store-level sales with SARIMAX, chronological validation and a historical Flask prototype.

    ACADEMIC PROJECT

    Forecasting · SARIMAX · Time Series

    GitHub

06 / CAPABILITIES

Tools and methods I use to
turn ideas into working systems.

01 / APPLIED AI

  • LLM Applications
  • Agent Orchestration
  • LangGraph
  • AI Observability
  • AI Automation

02 / MACHINE LEARNING

  • Regression
  • Classification
  • Gradient Boosting
  • Forecasting
  • Survival Analysis
  • Experimentation
  • Model Evaluation

03 / DATA

  • Python
  • SQL
  • Pandas
  • Power BI
  • Data Modeling
  • Data Pipelines
  • Data Quality

04 / ENGINEERING

  • Git & GitHub
  • Docker
  • Testing
  • MLflow
  • APIs
  • FastAPI
  • Streamlit
  • Automation

07 / CONTACT

Let's build
something useful.

I'm interested in opportunities and conversations around Data Science, Machine Learning and Applied AI.

I'll use these details only to reply to your contact.