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The individual will be part of the AAIOps team, responsible for shaping a state-of-the-art ecosystem (in terms of tools, technology and DataMart) for data, analytics & AI roles within SCMAC while aligning with wider SCB tech simplification effort. The individual will play a crucial part in operationalizing AI/ML models or other analytical pipeline at scale, ensuring efficient and reliable deployment across diverse environments.
Its responsibilities entail:
• Responsible for creation, maintenance, and successful execution of a machine learning operation & delivery (MLOps) ecosystem for the continuous delivery of AI artifacts (models, analyses, and predictions) developed by the SCMAC BA CoE, to WRB markets and to WRB digital solutions.
• Collaboration with a wide range of stakeholders including data scientists (SCMAC BA CoE), business analysts, governance, architect and software engineers (Enterprise Technology, CDO and WRB CIO Data Engineering teams) on the delivery of a fit-for-purpose big data ecosystem for building AI (ML/Gen AI) solutions in SCMAC BA CoE.
• Support the continuous improvement of the tools, technology, and data ecosystem available for all data roles in the SCMAC BA CoE.
• Implement best practices for version control, testing and CI/CD in ML pipelines
• Stay updated on emerging technologies and trends in MLOps, advanced AI (Gen AI) and cloud-based data and analytics platforms (Databricks, Dataiku).
• Responsible for developing and maintaining robust data workflows and pipelines using python and spark to process and analyse large-scale datasets to adopt new data feeds and feature stores, and in particular – incorporating our WRB unified data model (Athena) to reduce latency and improve the quality of data artifacts.
• Ensure solutions adhere to SCB’s model, risk, compliance and responsible AI standards.
Strategy
The individual will be part of the AAIOps team, responsible for shaping a state-of-the-art ecosystem (in terms of tools, technology and DataMart) for data, analytics & AI roles within SCMAC while aligning with wider SCB tech simplification effort. The individual will play a crucial part in operationalizing AI/ML models or other analytical pipeline at scale, ensuring efficient and reliable deployment across diverse environments.
Business
• Responsible for creation, maintenance, and successful execution of a machine learning operation & delivery (MLOps) ecosystem for the continuous delivery of AI artifacts (models, analyses, and predictions) developed by the SCMAC BA CoE, to WRB markets and to WRB digital solutions.
• Collaboration with both data scientists (SCMAC BA CoE) and software engineers (Enterprise Technology& WRB CIO Data Engineering teams) on the delivery of a fit-for-purpose big data ecosystem for building AI solutions in SCMAC BA CoE, transitioning from proprietary technology (SAS) to open-source technologies.
• Support the continuous improvement of the tools, technology, and data ecosystem available for all data roles in the SCMAC BA CoE.
• Implement best practices for version control, testing and CI/CD in ML pipelines
• Stay updated on emerging technologies and trends in MLOps, advanced AI (Gen AI) and cloud-based data and analytics platforms (Databricks, Dataiku).
• Responsible for developing robust data workflows and pipelines using python and pyspark to process and analyse large-scale datasets to adopt new data feeds and feature stores, and in particular – incorporating our WRB unified data model (Athena) to reduce latency and improve the quality of data artifacts.
Processes
• Continuously improve the operational efficiency and effectiveness of processes
• Ensure effective management of operational risks within the function and compliance with applicable internal policies, and external laws and regulations
People & Talent
• Collaborate with the team members on their work for better quality and accuracy
• Be able to work in agile fashion with other teams and support development /implementation of the solution
• Contribute towards training sessions for knowledge management
• Driving an environment of collaboration, both within CPBB Banking and across the wider Group, to ensure issues are raised and blockages are resolved in a timely manner
Risk Management
• Interpret the Group’s financial information, identify key issues based on this information and put in place appropriate controls and measures
• Ensure data security and data sharing in secured way through SharePoint in password protected files
Governance
• Awareness and understanding of the regulatory framework, in which the Group operates, and the regulatory requirements and expectations relevant to the role
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.
• Lead the [WRB to achieve the outcomes set out in the Bank’s Conduct Principles: [Fair Outcomes for Clients; Effective Financial Markets; Financial Crime Compliance; The Right Environment.]
• Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.
• Exercise authorities delegated by the Board of Directors and act in accordance with Articles of Association (or equivalent)
Key stakeholders
• Group/Region Analytics teams
• Group / Region/Country Product & Segment Teams
• Group / Region / Country Channels/distribution
• Group / Region / Country Risk Analytics Teams
• Group / Regional / Country Business Teams
• Support functions including Finance, Technology, Analytics Operation
Other Responsibilities
Embed Here for good and Group’s brand and values in WRB; Perform other responsibilities assigned under Group, Country, Business or Functional policies and procedures; Multiple functions (double hats); [List all responsibilities associated with the role]
• Bachelor's degree in computer science, information systems, engineering or data science
• Proficiency in Python and PySpark for both data processing and engineering tasks
• Knowledge of Azure DevOps (ADO)
• Understanding of machine learning concepts, model lifecycle management, model deployment processes.
• Experience in warehousing, ELT/ETL processes, SQL.
• Problem solving and Analytical Thinking
• Familiarity with Analytics Platforms like Dataiku, Databricks.
• Familiarity with Big data ecosystem and cloud computing
• Familiarity with cloud platforms like AWS, Azure, GCP
• Understanding of analytical and statistical methods
• Understanding of MLOps, LLMOPs pipelines.
• Big Data Management and Analytics
• Big Data Computing
• Logical Data Modelling
• Understanding of analytics lifecycle
• Data Science (Data understanding, feature engineering, model development etc.)
• DevOps
• Data Engineering
• AI/ML
We're an international bank, nimble enough to act, big enough for impact. For more than 170 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:
In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.
You'll no longer be considered for this role and your application will be removed from the employer's inbox.