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Fintech jobs: Data & AI - Work in Fintech Summit 24

Recording from the Work in Fintech Summit 2024, City of London. This panel on Fintech Jobs in Data and AI featured Ayaz Haji (Managing Director at BNY Mellon) and Theo Bell (Head of AI Product at Rimes), who shared their insights on career paths, innovation, and the evolving landscape of data and AI in financial services. Career Journeys: -Ayaz Haji started as a software engineer and transitioned into data and AI over a 20-year career in financial services. He is now leading transformation at BNY Mellon. -Theo Bell came from an engineering background and entered finance via a role at Goldman Sachs. He then moved into AI and product management at Rimes. Innovation in Financial Services: -Financial services have been at the forefront of tech innovation, especially in data and AI. However, it doesn't receive as much attention since many innovations are internal and not consumer-facing. -Financial institutions have massive tech budgets (e.g., over $10 billion annually), providing numerous opportunities for AI and data professionals. AI and Data in Fintech: -The panel discussed three "maturity curves" in fintech: software, data, and AI. While software is mature, data and AI are still evolving, especially in financial services. -Data is essential for AI, and poor data quality can severely impact AI outcomes. Theo emphasized that data governance and quality are critical in building AI products. Key Roles in Data and AI: -Data Engineers: Focus on building data pipelines and preparing data for analysis. -AI Engineers: Develop models and algorithms to provide business value. -Product Managers: Bridge the gap between technology and business, ensuring that AI solutions align with customer needs and business goals. Breaking into the Industry: -Internships are crucial for gaining experience and potentially securing full-time roles. If internships aren't possible, contributing to open-source projects or taking online courses (e.g., Coursera, Deep Learning courses) can help build a portfolio. -Ayaz and Theo stressed the importance of business value—understanding how data and AI projects contribute to the overall goals of the business. Challenges in AI: -A key challenge is data quality—poor data can lead to poor AI results. The panelists emphasized the importance of data hygiene (ensuring data is complete and accurate) and error tolerance depending on the application. Overall, the panel offered practical advice for those looking to enter fintech's data and AI space, emphasizing the need for continuous learning, internships, and understanding business value.   / matthewcheung50     / theo-bell-phd-b197102     / ayaz-haji-1b8b8411   Check out our website: https://workinfintech.com/ and subscribe to our mailing list to hear more about opportunities in fintech and web3 Follow our socials: Linkedin:   / work-in-fintech-global   Twitter:   / workinfintech   Youtube:    / @workinfintech   #startup #fintech #entrepreneur #data #ai #careers #careeradvice #careerdevelopment #students #aijobs #datajobs #datascience #rimes ‪@BNYMellonCareers‬ ‪@bnyglobal‬ ‪@GoldmanSachs‬