Qualifications

1. Educational Background: A university graduate from a top international institution, preferably with an MS or PhD. 2. Technical Mastery: Proven full stack software engineering capabilities, including hands-on experience with state-of-the-art AI technologies. Strong solutions architecture experience with complex enterprise solutions. 3. Industry Knowledge: Extensive experience in the financial services industry (retail, wholesale, investment banking, wealth management, etc.) with the ability to read and apply the latest academic and research findings. 4. Leadership Experience: Demonstrated track record of effective team leadership, including coaching, mentoring, and talent development. Ability to make tough decisions and achieve ambitious outcomes. 5. Communication Skills: Strong verbal and written communication skills; adept at delivering presentations to internal and external stakeholders. 6. Agile and DevOps Experience: Experience working in an Agile and DevOps-focused environment. Flexible and adaptable to changing requirements and responsibilities. 7. Functional/Technical Knowledge: 8. Machine Learning: Expertise in developing and deploying machine learning models, including data preprocessing, model training, evaluation, and optimization. 9. Cloud and Programming: Proficiency with cloud platforms and familiarity with multiple programming languages such as Python, Java, Node.js, and Golang. Experience with frameworks like Spring, Django, TensorFlow, and PyTorch. 10. Enterprise Solutions: Extensive experience in delivering scalable solutions within the finance industry, with hands-on delivery of digital products in large enterprises. What additional skills will be good to have? ? Innovation and Ecosystem Connectivity: Knowledge of Lean Startup Methodology and VC-style portfolio management. Experience with incubators, accelerators, VCs, and startups is a plus.