JOB SUMMARY
Standard Chartered Bank has embarked on an ambitious journey to revolutionize the Trade client digital journey by developing several client facing solutions that compete not just with the Financial Institutions but also with the new breed of Fintech companies. The revenue ambitions of the Trade business for 2023 are $1.4B and product & digital integration core to ensuring this vision is delivered and is responsible to drive the Trade data agenda with our corporate and institutional clients.
RESPONSIBILITIES
Strategy
Responsible and accountable to exploit the value of Trade Finance information assets and its analytics in cooperation with Transaction Banking Product, Digital Channels and Data Analytics (DCDA), Trade Operations and Technology
Lead strategy and the development of data and analytics products in cooperation with DCDA, Trade & Cash Product Development, Sales, Compliance and other to assure that solutions are aligned to the business strategy, released on time, on budget and with high quality.
Partner with product engineering heads to develop Data, Analytics and Innovation domain roadmaps, adoption of real time streaming and batch-processing platform/Hadoop platform
Support implementation of Cloud-based SaaS/PaaS/IaaS offerings for Data Solutions and leverage cloud enabled technologies and toolset for Data and Analytics domain
Influence Data & AI architecture governance strategy
The strategy alignment includes following pillars
Data Strategy (Data Sourcing, Data Quality, Data Visualization & consumption)
Machine Learning Pipeline / Tool Strategy / Platform Strategy
Third-Party Platform / in-house Strategy
Hosting Strategy for Data Analytics (In-House / Cloud Platforms)
Visualization and Data Democratization (Facilitate the evolution to self-service analytics and data preparation)
Business
Chief Product Owner for Data Initiatives
Develop roadmap to accelerate adoption of data analytics, Machine and AI within Trade Finance & working Capital Solutions across various domains incl. Operations, Sales, FCC, Fraud & Credit Risk
It should include (but not restrict to) prediction solution (e.g. Trade pricing) , recommendation solution (Cluster Analysis, Recommend Trade products to clients based on behaviour/profile), network analytics (Social Network analytics)and anomaly detection (Fraud)
Exploitation of big data and the liberation of data to the business, using a combination of open source, cloud and various tools and techniques for data analytics, machine learning, mining, and visualization.
Convert Analytic scope & roadmap into actionable deliverables (incl. User Stories & Verification)
Leverage of Analytics tools that utilize the data pipeline to provide actionable insights for the business users, operational efficiency
Increase Business AI understanding to increase adoption and acceptance
Support business in tracking and monitoring the commercialization process of initiatives
Processes
Innovation
Application of a broad and current industry perspective on technology trends/opportunities, alternate solution providers, leading practices, and our relative position
Demonstration of technology thought leadership, foster productive stakeholder relationships, and build strong sponsorship of our technology architecture and roadmap.
Understanding and influencing Open Account, Documentary Trade and Distribution strategy, ensuring it’s informed by current and emerging technology capability and supported by our architecture and roadmap
Evaluate vendors to find solution that best fit our functional and technical architecture
Incubation of various Data, ML & AI solution together with stakeholders from business & operations to constantly search for opportunities to increase sales, optimize processes and mitigate risk.
Support Strategic Initiatives and Partnerships
People & Talent
Build and lead data and analytics team for Trade Finance
Define job roles related to Data Science, recruit candidates (if needed) and manage a team of data and analytics leaders/members
Develop talent in Data across partners
Develop a learning environment & learning strategy based on formal training and training on-the-job. Train and upskill team (Data Engineering / Data Scientist / ML Experts / Business Intelligence
Foster teamwork, respect and collaboration across ITO function, DCDA and other stakeholders
Foster a culture of innovation. Build the appropriate culture and values to be a role model. Acquire new skills to keep up the system update to date and to align bank wide new initiatives
Data Analytics, Machine Learning & AI Delivery
Drive and manage the development and deployment of Trade and Working Capital data and analytics platform.
Incubate and propose innovative solution to business and stakeholders
Design analytical solutions/experiments to solve various strategic business problems in Trade Finance and Working Capital through engagement and research
Data squads to manage and deliver the lifecycle of a data science projects across four phases
Data management & Data sourcing
Data Engineering & Data Science
Machine Learning & Analytics
Data Visualization & Provision of AI microservices endpoints for consumptions
Develop and communicate data analytics, ML & AI vision that supports the broader organizational vision
Ensure team culture consistently demonstrates alignment with SCB principles and its aligned to SCB’s business and technology strategy. Influence your team’s technical and business strategy by making insightful contributions to team priorities and approach.
Own the development, implementation, and delivery of successful large-scale project
Manage cost effective delivery of data to respective teams which are up-to-date, comprehensive, and easy to consume (incl. data dictionary, feature engineering), which includes big data (structured and unstructured) as well as provision of transactional data
Take the lead in identifying and solving ambiguous problems, architecture deficiencies, or areas where your team’s software bottlenecks the innovation of other teams. Make solutions simpler and reusable.
Governance and Responsible AI
Feedback data and analytics oversight on data governance to executive sponsorship, business, and risk committee (e.g. Sustainability Refinement or NFRC Technology Working group)
Ensure all regulatory, compliance and internal control requirements are met. Develop and execute plans for QPR approval to mitigate any risk / non-compliances
Identify and standardize the use and governance of data and analytics in support of the enterprise's business strategy.
Responsible AI – incl. the governance of data and algorithms used for analysis, analytical applications and automated decision making in TB. Ensure that model used are responsible and explainable. Manage Responsible AI as Business Risk Owner for Trade Finance
Ensure data quality (DQMF) is applied for data analytics and AI projects
Adherence to Risk & Data Quality Management Requirements
Risk and Audit Continuous management of the Trade Application System risk
Proactively identify issues and actions
Monitor and remediate issues and actions from audits
Awareness of the regulatory requirements and ensuring these are catered for in the platform design
Portfolio Management Planning & Budget
Identify, prioritize and execute the data and analytic initiatives with clear line of sight to enterprise strategies and business outcomes incl. revenues, cost efficiencies & risk mitigation
Maintenance of Trade Finance level data, AI & ML technology roadmaps encompassing application and related infrastructure services.
Delivery within given budget, management of internal and external cost and strive for optimal delivery and sourcing solutions
Processes & New Ways of Working
CCIB moved to the New Ways of Working and the delivery is managed in squads lead by the Product Owner and/or augmented by Subject Matter Expert, Business Analysts, Developers, and testers. Therefore, ensure that data, ML & AI solutions is delivered in the spirit of New Ways of Working
CPO to present and report book of work in QPR/MPR
Support data refinement session in order to agree on next 90 days deliverables. Manage and support the LuW process for data analytics, ML & AI related enhancements
Always optimize accuracy & velocity of squads
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
Regulatory & Business Conduct
Display exemplary conduct and live by the Group’s Values and Code of Conduct.
Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.
Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.
Key Stakeholders
Technology Engineering teams in Trade
Trade Solution Engineering Team
Architect
DCDA
Product Management Cash, Trade & Working Capital Solutions
FSCO / Compliance teams
Stakeholder Management
Coordinate with resources and teams across different locations
Capability development/mentor team members
Other Responsibilities
Embed Here for good and Group’s brand and values, Perform other responsibilities assigned under Group, Country, Business or Functional policies and procedures; Multiple functions (double hats)
Our Ideal Candidate
Degree in Software Engineering, IT, Computer Science, or related fields. Degree in computer science, engineering, applied mathematics or have a degree in other related IT fields.
10+ years experience with a proven track record of working in the product management or channel management functions in Trade Finance/Transaction banking.
5+ years of working experience in data ecosystem (Spark, Python/Scala, TensorFlow) with on Data Science, Machine Learning and Artificial Intelligence
5+ Experience in Transaction Banking domain; Good Understanding of Trade Finance, Working Capital Solutions and Cash Management
Experience in working in an agile environment
Very good understanding of Machine Learning models such as Recurrent Neural Networks, Network Analytics, Regression, Anomaly Detection & Clustering
Understanding of multiple programming languages, especially related to Data Science (Python, Scala, TensorFlow, R)
Understanding of distributed platforms Apache Spark, Data Warehouse, Apache Hadoop, Amazon Web Services (AWS), ETL (extra, transform, load), Big data analytic. Data visualization technologies, Data mining of social media data, Risk modelling, Artificial Intelligence
Related Data Engineer/Analyst certifications are beneficial (e.g. AWS / Azure Solution Architect, IBM Certified Data Engineer, AWS & Azure Machine Learning / AI specialist etc.)
Comprehensive functional and technical knowledge in Transaction Banking through practical experience in defining and delivering technology solutions
Current and deep Data and Analytics domain market insights.
Strongly developed strategic, analytical and communication skills evidenced by experience in formulating strategic scenarios, evaluating trade-offs within a robust commercial framework, developing related financial models and designing practical execution plans.
Ability to synthesize complex issues/scenarios into easy-to-understand concepts
Demonstrated analytical ability, problem deconstruction, statistical competency, meticulous analysis skills, data validation, and scientific rigor
Fluency in a range of statistical data analysis and machine learning
Effective communication skills
Role Specific Technical Competencies
Pertinent first-hand experience and a proven track record of working in the product management and development functions in Transaction banking or Data Science
Good understanding of the product development lifecycle using Agile Methodology and relevant prior experience in drafting vision statements, epics and user stories, use cases documents, solution papers, business workflow documents and high-level design documents.
Deep understanding of the transaction banking domain with a profound ability to conceive and design end-to-end product flows, define interface requirements, identify relevant operational processes and clearly articulate these flows and processes to the relevant business and technology workgroups.
Very good understanding of Machine Learning models such as Recurrent Neural Networks, Network Analytics, Regression, Anomaly Detection & Clustering
Understanding of technology; proven ability to translate technology possibilities and solutions to business / client usage opportunities will be an added advantage.
About Standard Chartered
We're an international bank, nimble enough to act, big enough for impact. For more than 160 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents. And we can't wait to see the talents you can bring us.
Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion. Together we:
Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
Be better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term
In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.
Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations
Time-off including annual, parental/maternity (20 weeks), sabbatical (12 weeks maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum
Flexible working options based around home and office locations, with flexible working patterns
Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning
Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.
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Visit our careers website www.sc.com/careers