Lead the strategic direction and execution of Data Science and AI initiatives within the organization. This role is pivotal in driving functional excellence, fostering innovation, and ensuring long-term growth through advanced analytics and intelligent solutions. Focus on building and mentoring high-performing teams, developing cutting-edge AI capabilities, and establishing robust governance frameworks.

This position demands a visionary leader to define and implement the organization's Data Science and AI strategy, aligning it with overarching business objectives and product vision. You will be instrumental in shaping the future of AI-driven products and services, particularly within the financial services sector.

Develop and execute the organization's Data Science and AI strategy. Lead, build, and mentor high-performing Data Science and Machine Learning teams, fostering a culture of innovation and scientific rigor.

Own the end-to-end data modeling strategy, ensuring statistical soundness, scalability, and reliability. Drive the Machine Learning roadmap across various AI domains, including deep learning, generative AI, and predictive analytics. Guide teams in selecting appropriate algorithms and deployment strategies for production-grade AI solutions.

Establish enterprise-wide standards for model development, deployment, and governance. Champion responsible and trustworthy AI practices, ensuring fairness, explainability, and compliance. Drive the development of intelligent financial services capabilities, focusing on areas like credit risk, fraud detection, and decision intelligence.

A minimum of 12 years of experience in Data Science, Machine Learning, AI, or Statistical Modelling, with proven leadership experience in managing Data Science organizations. Expertise in statistics, machine learning, predictive analytics, and experimental design is essential.

Proficiency in Python and modern ML frameworks (Scikit-learn, TensorFlow, PyTorch) is required, along with hands-on experience designing and deploying enterprise-scale ML solutions. Strong SQL skills and experience with large-scale datasets are also necessary.

Deep understanding of MLOps practices, Responsible AI principles, and AI/Model Governance frameworks. Prior experience in financial services, particularly in lending or credit risk, is highly preferred. Excellent leadership, communication, and stakeholder management skills are crucial for effectively collaborating with diverse teams and senior leaders.