Head of Data Platform, Data and Analytics PINF, HSBC Fintech

Key Skills

Aartificial intelligence, AWS, Computer Vision (CV), Data Analytics, Data Lake, Data science techniques, Deep Learning, Google Cloud Platform (GCP), Java Programming, Large scale deployment, Machine learning techniques, Natural Language Processing (NLP), Python Programming, R Programming, SAS, Scala Programming, Statistics

Job Description

Contribute to the establishment of consistent, best-in-class Analytics capability supporting the RBWM 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 & analysts, 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.

Mature advanced analytics capabilities that further enable the personalisation and increased relevance of customer experiences, across all channel touch points.

Enable and execute sales performance productivity analytics

External data collaboration and commercialization

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

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.

Requirements

• To be successful in the role, you should meet the following requirements:
• 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.