Fernando Barontini Email & Phone Number

São Paulo, São Paulo, Brasil

While at Recovery, I was fortunate to contribute to a variety of data-driven initiatives across multiple teams.I spearheaded the development of a Python and Databricks-powered honorarium engine, which automates the calculation of payments to our partner collection agencies at the point of agreement generation. This solution significantly improved operational efficiency by reducing payment processing time from 11 days to 8 days, and by decreasing disputes by over 99%. Consequently, we realized a monthly revenue increase of R$2 million.In my current position, I am leading the development and optimization of our pricing engine. This robust system is capable of processing millions of pricing decisions for our entire customer base in a fraction of the previous time.

São Paulo, Brasil

São Paulo, Brasil

São Paulo

São Paulo

For over 6 years, I have been dedicated to driving credit recovery efforts across both retail and wholesale sectors. My expertise lies in designing and implementing innovative solutions to streamline processes and maximize recovery rates.In the retail segment, I pioneered the development of predictive collection score models, leveraging machine learning to significantly boost recovery rates. Additionally, I crafted a suite of customized reports to provide actionable insights into the performance of negotiated agreements. By automating case assignment, I optimized workload distribution and reduced case resolution time to a matter of hours.In the wholesale domain, I architected a litigation case management system, harnessing the power of IBM Watson and Google Vision (OCR) to automate document analysis and accelerate decision-making. Through ongoing monitoring of the litigation credit portfolio, I identified strategic negotiation opportunities and minimized losses.As a results-oriented professional, I am adept at leveraging data analytics and emerging technologies to drive operational efficiency and deliver exceptional outcomes.

São Paulo

Experiência no desenvolvimento de modelos de risco para prevenção de possíveis clientes mau pagadores e onboarding de novos clientes.Especializado em ETL das informações do banco de dados Oracle para geração de relatórios de acompanhamento das safras de credito.Criação e acompanhamento das políticas de crédito e cobrança dos clientes.

Santo André, São Paulo, Brasil

MIS de Risco e Gestão de ConsumoExtração de dados para desenvolvimento de aplicações voltadas aos usuários de fraude e gestão de consumoAutomatização de relatórios gerenciais.

Machine Learning, Artificial Intelligence

Análise de Big Data via Machine Learning, com 76 horas de duração.

Machine Learning, Artificial Intelligence

Fundamentos Em Data Science

Cênica Da Computação, Computer Science

Education record