Tiago Gimenez

I’m a highly skilled Data Scientist with a solid background in fraud prevention, driven by a passion for solving complex challenges and safeguarding financial ecosystems. I hold a Bachelor’s degree in Statistics from the University of Campinas, one of the top universities in Latin America, and over 6 years of hands-on experience in the payment and financial sectors.

💡 What I do best:

- Building and improving fraud prevention systems: From designing fully automated systems that prevent card fraud attacks to crafting realtime decision models. I’ve been at the forefront of protecting businesses from fraudulent activities.

- Driving accuracy and impact: With achievements like maintaining a 99%+ true positive rate in rule application and a 98% recall in fraud detection systems, I focus on actionable results.

- Strategic antifraud design: I contributed to developing secure and scalable fraud prevention strategies for emerging banking products.

🔍 Key achievements I’m proud of:

- Developed realtime antifraud transaction decision rules with over 99% assertiveness, effectively minimizing fraud impacts while ensuring no friction for legitimate transactions.

- Built an identity theft detection system with zero false positives at Stone, leading to the automatic removal of 4000+ fraudulent accounts in just two months.

- Investigated social engineering fraud schemes and prevented account takeover cashout operations at Stone, getting expertise in cybersecurity and information security.

- Reduced error rates in fraud detection by 50% at Cielo, leveraging data driven rules that significantly lowered chargeback rates.

🛠️ Technical toolkit:

- Programming Languages: Python, SQL and R.

- Machine Learning Models: Regressions, tree-based models and neural networks.

- Other Skills: Statistical analysis, data exploration, data mining, predictive modeling, etc.

💻 Github: github.com/tiagogimenez

linkedin.com/in/gimeneztiago