Job Summary

Role Purpose

Ensure the safe, reliable and compliant operation of data pipelines and AI/ML solutions across the bank by:

• Proactively monitoring data quality, data flows and AI/ML model performance in production.
• Detecting and escalating issues early (e.g., data breaks, model drift, bias, performance degradation).
• Coordinating remediation with Technology, Data, and Business/Risk owners.
• Supporting adherence to model risk, data governance and regulatory requirements for AI.

The role acts as the “control tower” for live data & AI operations, helping to maintain trust, stability and compliance in all AI‑enabled processes

Key Responsibilities

Strategy

• Data & Model Monitoring Operations
• Operate and enhance monitoring frameworks for production data pipelines and AI/ML models.
• Track key indicators such as:
• Data availability, timeliness, completeness, consistency and accuracy
• Model performance (e.g., accuracy, AUC, precision/recall, stability, error rates)
• Model and data drift, out‑of‑distribution behaviour, and bias indicators.
• Review monitoring dashboards and alerts; triage and prioritise issues based on risk and impact.

Business

• Identify opportunities to enhance monitoring coverage, automation and alert quality (reducing false positives/negatives).
• Partner with Engineering and AI CoE teams to improve observability tooling (e.g., logging, metrics, tracing, model monitoring platforms).
• Contribute to the design and testing of new monitoring controls for emerging AI use cases (e.g., generative AI, NLP, real‑time scoring).

Processes

• Runbook & Process Management
• Develop and maintain standard operating procedures (SOPs), runbooks and playbooks for data & AI monitoring and incident response.
• Document common failure modes, known issues and standard resolutions.
• Continuously refine processes to improve speed, quality and consistency of responses.

People & Talent

• Lead through example and demonstrate the bank’s culture and values

Risk Management

• Incident Management & Issue Resolution  Act as first‑line operations contact for data and AI incidents (e.g., failed data loads, broken features, degraded model performance).
• Perform initial root cause analysis using logs, metrics, and runbooks.
• Coordinate with Data Engineering, Model Development, IT Operations and Business/Risk owners to remediate issues.
• Log incidents, track actions, and ensure timely closure in line with SLAs.
• Escalate material issues in accordance with risk, compliance and operational incident frameworks

Governance

• Execute regular control checks on:
• Data quality thresholds and exceptions
• Model performance thresholds and usage limits
• Access controls and entitlements for data and AI systems.
• Support adherence to model risk management and data governance policies.
• Maintain evidence and artefacts for audits, regulatory reviews and internal governance forums.
• Contribute operational input into model review committees and data governance forums

Key Responsibilities

Reporting & Stakeholder Communication

• Stakeholder & Domain Leadership
• Act as primary interface between business stakeholders, CDO, and Technology
• Engage senior stakeholders to:
• align priorities
• drive adoption
• manage regulatory expectations

Key stakeholders

• Data & Analytics           
• GenAI Specialists         
• AI Operations                  
• Business Units
• Technology (AI Engineering Lead; Data Engineering Lead; platform owners)
• Functions CDO stakeholders (standards, platform, data foundations)
• AI Services
• Legal, Privacy, Cyber Security, Model Risk, Operational Risk
• Internal Audit / Assurance partners
• COO / Finance partners (capacity and investment planning)
• AI Solutions Team
• Compliance & Governance

Other Responsibilities

• Degree in Information Technology, Computer Science, Data/Analytics, Engineering, or related discipline.
• Certifications in IT operations, data management, cloud operations, or model risk/governance are an advantage
• Extensive programming experience using SQL, Python, SAS, Excel Automation.
• Strong analytical mindset with excellent analytical, logical, reasoning and problem-solving skills.
• Excellent written and oral communication skills at all levels (i.e. colleagues to senior management) and situations (i.e. one-on-one to presentations)
• Exposure to advanced machine learning methodologies is a plus

Skills and Experience

Technical & Operational Skills

• Experience In Monitoring And Operating Data Platforms, Analytics Systems, Or Ai/Ml Solutions In Production.
• Familiarity With:
  • • Data Platforms And Query Tools (E.G., Sql‑Based Systems, Data Warehouses/Lakes).
    • Monitoring/Observability Tools (E.G., Dashboards, Alerting Platforms, Logging Tools).
    • Basic Understanding Of Ml Concepts And Model Performance Metrics.
• Ability To Read and Interpret Logs, Metrics, And Dashboards To Diagnose Issues.
• Understanding Of Data Quality Frameworks, Controls, And Common Data Issues.
• Experience With Ticketing/Incident Management Tools And It Service Management (Itsm) Processes.

Risk, Control & Governance Awareness

• Good Understanding of Operational Risk, Model Risk And Data Governance Concepts.
• Awareness Of Regulatory Expectations Concerning Use of Data And Ai In Financial Services.
• Strong Control Mindset with Attention To Documentation, Evidence, And Auditability.

Analytical & Problem-Solving Skills

• Structured Approach To Incident Investigation And Root Cause Analysis.
• Ability To Prioritise Issues Based On Risk And Business Impact.
• Comfortable Working With Incomplete Information And Driving Issues To Closure.

Stakeholder & Communication Skills

• Clear, Concise Communication Style, Able To Explain Technical Issues To Non‑Technical Stakeholders.
• Experience Collaborating With Cross‑Functional Teams (Technology, Data, Ai, Risk, Compliance, Business).
• Calm And Professional Under Pressure, Especially During High‑Severity Incidents.

Personal Attributes

• High Integrity, Strong Sense Of Accountability And Ownership.
• Detail‑Oriented With A Focus On Accuracy And Reliability.
• Proactive, Curious And Willing To Learn About New Ai/Ml And Data Technologies.
• Adaptable, With A Continuous Improvement Mindset.

Skills and Experience

• GenAI/agentic concepts
• Product & portfolio management (intake, prioritisation, lifecycle, adoption)
• AI risk management literacy (validation, drift/monitoring concepts)
• Stakeholder management and operating model design
• GenAI/agentic concepts
• Product & portfolio management (intake, prioritisation, lifecycle, adoption)

About Standard Chartered

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:

• 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
• Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term

What we offer

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 leave, parental/maternity (20 weeks), sabbatical (12 months 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.