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Private Credit Senior Vice President
Private Credit Senior Vice President
New mentor!
Member since 2026
  • São Paulo
About the mentor

Gabriel Pires is a Senior Data Scientist and Quantitative Modeling Specialist, with a career defined by the integration of data science, artificial intelligence, quantitative finance, and risk management, primarily within the Brazilian financial, pension, and capital markets. His professional trajectory combines strong academic training, hands-on experience in highly regulated environments, and the development of advanced models applied to strategic decision-making.

Current Professional Role

Since 2025, Gabriel has been working as Quantitative Modeling, where he is responsible for the development and evolution of analytical solutions focused on credit risk and fixed income. His main responsibilities include:

  • Development of clustering models for credit bounds, providing new perspectives on credit risk;
  • Construction of corporate, sectoral, and issuer-level credit curves, used as proxies for CDS;
  • Enhancement of the Credit Curve, including callable bonds and methodological refactoring;
  • Implementation of Z-spread calculations applied to credit bounds;
  • Creation of monitoring dashboards for credit and fixed income, focused on detecting out-of-pattern market movements;
  • Deployment of models to production in Databricks and AWS, including version control, governance, model risk management, and MLOps practices.
  • Clustering studies of Brazilian investment funds and asset managers, using market metrics and machine learning to produce more representative classifications;
  • Development of synthetic benchmarks through mathematical modeling of time series;
  • Leadership of a Generative AI project applied to self-regulatory documents, aimed at supporting member inquiries;
  • Creation of a text classification model using embeddings for the automatic categorization of customer service requests;
  • Acting as a bridge between business areas and technical teams, facilitating meetings and strategic alignment.

Experience in Risk Management and Quantitative Finance

Gabriel worked as a Quantitative Risk Analyst. During this period, he developed high-impact institutional solutions, including:

  • Creation of a Systemic Risk model for the Brazilian economy based on machine learning, presented at five events and awarded the Financial Innovation Award 2023 (CFA Institute);
  • Development of portfolio optimization models used to define risk limits across 14 pension plans;
  • Implementation of an NTN-B optimization model, aligned with PREVIC standards, applied to all immunized plans;
  • Construction of IPCA inflation forecasting models using domestic macroeconomic variables, supporting medium- and long-term strategic decisions;
  • Modeling of interest rate simulations based on an adapted RiskMetrics methodology;
  • Development of Credit and Liquidity VaR, as well as deep learning models for distribution simulation, risk metrics, and correlation matrices;
  • Active participation in an Innovation and AI Working Group, promoting a data-driven culture and identifying organizational bottlenecks.

Experience in Energy and Data Analytics

Gabriel also worked as a Data and Risk Analyst, operating in both Brazil and Chile. His key contributions include:

  • Quantitative studies to support trading desk strategies, leading to more informed and effective decisions;
  • Development and maintenance of VaR, CVaR, stop-loss, and P&L control models, mitigating significant monthly losses;
  • Creation of a customer geolocation project, generating approximately 10,000 leads;
  • Development of energy consumption forecasting models for current and prospective clients, directly applied by the commercial team;
  • Implementation of end-to-end ETL pipelines, using Python, SQL, APIs, web scraping, and Power BI for portfolio visualization and monitoring;
  • Maintenance of energy pricing processes and portfolio visualization for the Chilean market.

Academic Background and Scientific Research

Gabriel has a strong and multidisciplinary academic background:

  • PhD in Artificial Intelligence – UNESP (2026–2030)

Thesis: Magic Bullet for forecasting macroeconomic variables: development of a state-of-the-art neural network for the Brazilian economy;

  • Master’s Degree in Artificial Intelligence – UNESP (2023–2025)

Dissertation: Deep Learning and Metaheuristics: An Approach to Portfolio Optimization;

  • Bachelor’s Degree in Chemistry – University of São Paulo (USP) (2016–2021)

Undergraduate Project: Synthesis of Reversible Covalent Inhibitors of SARS-CoV-2 Mpro.

Skills and Professional Profile

Gabriel has C1-level English proficiency, strong command of Python, SQL, and C, experience with AWS, Azure, Oracle, and MySQL, and a proven ability to translate complex business problems into mathematical models and scalable AI solutions.

Expertise
  • Quant
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