Job Summary
The Head of Data & AI at AEON Bank will be responsible for defining and executing the data and artificial intelligence strategy. This role involves leading a team to build scalable data infrastructure, develop advanced analytics capabilities, and implement AI-driven solutions to enhance customer experience, optimize operations, and drive business growth. The ideal candidate will have a strong background in data science, machine learning, and data governance, with a proven ability to translate complex data insights into actionable business strategies within the financial services industry.
Job Responsibilities
- Develop and implement a comprehensive data and AI strategy aligned with AEON Bank's business objectives.
- Lead the design, development, and maintenance of robust and scalable data infrastructure, including data warehousing, data lakes, and real-time data processing systems.
- Oversee the entire lifecycle of AI/ML models, from conception and development to deployment, monitoring, and optimization.
- Build, mentor, and manage a high-performing team of data scientists, data engineers, and AI specialists.
- Establish and enforce data governance policies, standards, and best practices to ensure data quality, security, privacy, and compliance with regulatory requirements.
- Drive the adoption of data-driven decision-making across the organization by providing actionable insights and developing predictive models for various business functions (e.g., credit scoring, fraud detection, marketing personalization, risk management).
- Collaborate closely with business units, product development, and IT teams to identify opportunities for leveraging data and AI to solve business problems and create innovative solutions.
- Stay abreast of the latest trends and technologies in data science, machine learning, and artificial intelligence, and evaluate their applicability to the bank's strategy.
- Manage relationships with external vendors and partners for data and AI-related services and tools.
Job Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field. A Ph.D. is a plus.
- Minimum of 10 years of experience in data analytics, data science, or AI roles, with at least 5 years in a leadership or management position, preferably within the banking or financial technology (FinTech) sector.
- Deep expertise in data warehousing, ETL processes, big data technologies (e.g., Hadoop, Spark, Kafka), and cloud platforms (e.g., AWS, Azure, GCP).
- Strong proficiency in programming languages commonly used in data science (e.g., Python, R, Scala) and SQL.
- Extensive experience with various machine learning algorithms, statistical modelling, and predictive analytics techniques.
- Proven track record of successfully delivering end-to-end data and AI projects that have driven tangible business outcomes.
- Solid understanding of data governance, data quality management, and data security principles, especially within a regulated industry.
- Excellent leadership, communication, and interpersonal skills with the ability to articulate complex technical concepts to non-technical stakeholders.
- Strategic thinker with a strong business acumen and a passion for leveraging data and AI to solve real-world problems.
- Experience with agile development methodologies.
