Lead Vice Precident - Decision Sciences - GAC WPB PINNACLE

• Converse both in technical and business language across the stakeholder matrix.
• Design, architect and manage analytics processes and infrastructure and define initiatives with senior management; Interface with the business to increase awareness on how to leverage advanced analytics tools and techniques by business communities.
• Contribute to the establishment of consistent, best-in-class Analytics capability supporting the WPB ASP HSBC Insurance business but also simultaneously joining up with the rest of the HSBC Group.
• Architect end-to-end analytics solutions from collaborating with IT on proper data infrastructure, to assemble and perform data science techniques, to integrate such solution into the overall technology environment for production in a highly digital environment.
• Manage a direct team of data scientists & engineers, pioneer innovation by proactively linking new data & analytics trend to business need, and proactively drive in-house data science capability specifically in areas of sophisticated machine learning, deep learning and AI, provide thought leadership and delivery management on daily basis.
• Enforce and monitor standards for the application of analytics across the businesses.
• Scope and define analytics need from stakeholders, deliver towards a data and analytics agenda on annual and ongoing basis and mobilize resources in the CoE to carry out such plans.
• Enable and execute sales performance productivity analytics.
• External data collaboration and commercialization.
• Lead the decision sciences practice with high quality analytical solutions for the business stakeholders across one of more regions; Mature advanced analytics capabilities that further enable the personalisation and increased relevance of customer experiences, across all channel touch points.
• Establish and maintain a global best practice sharing environment for all aspects of new advanced analytics capabilities, new data sources as well as relevant fintech capabilities.
• Supports innovative analytical thinking & solutions that results into improved business performance.
• Embrace market / industry best practices and bring-in best-in-class and relevant solutions for better business decisions.
• The role holder shall also be expected to guide and lead team members from a functional perspective and help them build up a strong business understanding.

• 12+ years of experience of using statistical concepts & machine learning models to solve complex business problems.
• At least Master's degree in Mathematics, Statistics, Economics, Engineering, Computer Science, Management or other quantitative fields of study.
• Proven experience in building and leading a modelling and analytics function in a large scale organization.
• Prior experience in building models and quantitative solutions.
• Collaborate with leaders to drive usage of analytics services by various business communities.
• Develop and enhance the capability and expertise of the team by providing the effective coaching and on-job training.
• Build a culture committed to the delivery of outstanding customer service and open, transparent, honest team environment.
• Effectively engage in a matrix structure to drive transformation goals for the organization.
• Excellent written and verbal communication skills. Ability to develop and effectively communicate complex concepts and ideas.
• Execute for results and build diverse teams.
• Master or PhD in relevant quantitative disciplines such as Statistics, Mathematics, Computer Science, Engineering, Operations Research, Physics or a related discipline with a focus on use of analytics and optimization to influence business decisions.
• Experienced in leveraging business analytics and machine learning algorithm to drive business growth, identify product proposition or enhance retail banking customer journey, etc.
• Hands-on knowledge in one of the following data analytics domains: machine learning, natural language processing/generation, computer vision, deep learning and advanced analytics.
• Strong retail banking and/or life insurance products or wealth management business knowledge and knowledge of profitability model.
• Experience in working with cloud-based data ecosystems (e.g. data lake, AWS, GCP, etc.). Scripting language capabilities in Python, R, SAS, Java or Scala.
• Able to translate complex business problems into analytical requirements and propose actionable solutions based on internal and external best practice.

HSBC