Director of Data Science (Ethoca)

Join Mastercard as the Director of Data Science for Ethoca, where you will lead the development and delivery of advanced AI and machine learning solutions. This senior leadership role involves defining the data science strategy, guiding execution across multiple business initiatives, and ensuring solutions are delivered at scale. You will mentor and inspire a high-performing data science team, partner with product, engineering, and business leaders, and provide hands-on technical leadership in model development, deployment, and governance.

• Definir y ejecutar la visión y la hoja de ruta de la ciencia de datos para la mejora del producto, alineando las iniciativas con las prioridades comerciales y la estrategia del producto.
• Liderar, mentorear e inspirar a un equipo de ciencia de datos de alto rendimiento, fomentando una cultura de excelencia técnica, innovación y colaboración.
• Colaborar con líderes de producto, ingeniería y negocios para dar forma a los requisitos y entregar capacidades impulsadas por datos que mejoren la experiencia del cliente y reduzcan las disputas.
• Strong track record of translating complex data problems into scalable, measurable business outcomes
• Deep expertise in supervised, unsupervised, and generative AI methods, with strong understanding of their mathematical foundations
• Proven experience leading data science teams and delivering enterprise-scale AI/ML solutions
• Hands-on background in NLP, information extraction, or computer vision or multi-modal AI applied to real-world business challenges
• Proficiency in Python, ML frameworks (Scikit-learn, PyTorch, TensorFlow), SQL, Spark, and Azure ML/Snowflake
• Master’s degree required; PhD preferred
• Skilled at engaging with senior stakeholders, presenting technical results to diverse audiences, and driving alignment across functions
• Experience working in highly regulated industries, with an emphasis on data governance and compliance
• Prior patents or publications in AI/ML
• Experience in payments, FinTech, or consumer transaction data
• Demonstrated success applying GenAI or multi-agent systems in production environments