About Advanced Data Science Roles Our team is a leading payment and fintech company operating in 50+ high-growth markets across Asia, Central and Eastern Europe, Latin America, the Middle East, and Africa. We strive to build a world without financial borders where everyone can prosper. We support over 400 payment methods and PCI-certified platforms, processing approximately 6 million payments daily. About this role - You will play a key part in designing and deploying advanced data science solutions to identify, analyze, and mitigate fraud and risks in the Latin American market. - This is a hands-on position emphasizing modeling, experimentation, and analytical problem-solving. Main responsibilities - Lead technical initiatives within the Data Science team in Fraud Prevention for Latin America, establishing standards for modeling and analytical rigor. - Define technical strategies for key projects, mentor team members, and review model design, code, and evaluation methods. - Collaborate with cross-functional teams to translate complex business problems into effective data science solutions. - Design and deploy machine learning models for fraud detection, aligning innovation with business goals, robustness, and scalability. - Develop and maintain data pipelines using tools like DBT and Snowflake to ensure high-quality data for modeling and analytics. - Create dashboards and monitoring tools in Tableau, Power BI, or Kibana to facilitate data-driven decision-making and monitor fraud trends. Requirements - Bachelor's degree in engineering, mathematics, economics, statistics, or related fields. - At least 4 years of experience in data science. - Hands-on experience developing, training, and deploying machine learning models. - Proficiency in SQL for data exploration and transformation. - Strong skills in Python and its data science ecosystem. - Experience with data visualization platforms such as Tableau, Power BI, or Kibana. - Excellent command of English. - Experience in data modeling and designing data structures for analytical and machine learning purposes. Bonus points if you have: - Familiarity with cloud-based technologies. - Knowledge of DevOps practices.