Job Description
JOB PURPOSE
The Chief Data Scientist leads the development and execution of the Bank’s data science and AI strategy. This role drives the application of advanced analytics, machine learning, and data-driven solutions to enhance decision-making, improve risk management, and strengthen customer experience. The Chief Data Scientist also acts as a strategic advisor to senior management and promotes a culture of innovation and data-driven thinking across the organization.
KEY RESPONSIBILITIES
1. Strategy & Leadership
Define and implement enterprise-wide data science and AI strategy aligned with business priorities.
Advise senior executives on leveraging data for business growth, efficiency, and risk management.
Drive execution of the AI/data roadmap and measure business impact.
2. Model Development & Innovation
Lead design, validation, and deployment of predictive and AI/ML models (e.g., credit scoring, fraud detection, customer segmentation).
Ensure model governance, compliance, and performance monitoring.
Foster continuous innovation through new AI applications and analytical use cases.
3. Data & Technology Enablement
Collaborate with IT and Data Engineering to build scalable data platforms, pipelines, and AI/ML infrastructure.
Ensure data quality, integrity, and accessibility across the Bank.
4. Governance & Compliance
Establish ethical AI practices and ensure compliance with data privacy, regulatory, and security requirements.
5. Business Partnership
Partner with business units to identify and execute high-impact, data-driven initiatives.
Translate analytical insights into clear, actionable business recommendations.
6. People & Culture
Build and develop a high-performing data science team.
Promote collaboration, innovation, and accountability.
Act as a role model in reinforcing the Bank’s corporate culture and values.
Job Requirements
1. Educational Qualifications
• Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2. Relevant Knowledge / Expertise
• At least 10 years of experience in data science or advanced analytics, including a minimum of 5 years in a leadership role.
• Proven track record in building and deploying machine learning and AI models in large-scale production environments.
• Deep expertise in statistical modeling, machine learning, deep learning, natural language processing (NLP), and big data technologies.
3. Skills and Competencies
• Proficiency in programming languages such as Python, R, and SQL; experience with distributed computing frameworks (e.g., Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
• Strong leadership, stakeholder management, and communication skills, with the ability to influence and engage effectively at the executive level.