Specialist, Data, Analytics & AI

standardchartered

Chennai, India NM Years Exp Posted 79d ago

Use Case Formulation & Solution Design

Collaborate with Risk and Compliance stakeholders to translate business problems into clearly defined analytics/ML use cases with measurable outcomes.
Conduct feasibility assessments, including data availability, model ability, risks, and expected value.
Develop solution designs and model blueprints, including data pipelines, features, algorithms, controls, and monitoring approach.

Model Development & Implementation

Design, build, and validate statistical and machine learning models for areas such as:
- Credit risk scoring and early warning indicators
- Financial crime (AML, fraud detection, sanctions screening enhancements)
- Conduct risk and compliance surveillance
- Operational and cyber risk analytics
Implement models using appropriate tools and frameworks (e.g., Python, R, SQL, Spark) following the bank’s model risk and development standards.
Ensure models are explainable, auditable, and compliant with model governance, regulatory expectations, and ethical AI principles.
Partner with Technology/Data Engineering to productionize models and integrate them into business workflows and platforms.

Data Management & Feature Engineering

Source, explore, and assess the quality of internal and external datasets relevant to risk and compliance.
Design and implement robust data preprocessing, feature engineering, and variable selection pipelines.
Ensure data usage adheres to data privacy, security, and governance standards.

Model Validation, Monitoring & Governance

Define, implement, and document model performance metrics and validation approaches (e.g., accuracy, stability, fairness, drift).
Support internal model validation, audit, and regulatory reviews by providing clear documentation and technical explanations.
Design monitoring dashboards and processes to track model performance, drift, and usage; proactively recommend recalibration or redevelopment where needed.
Ensure adherence to model risk policies, governance frameworks, and regulatory guidelines for AI and advanced analytics.

Key Responsibilities

Stakeholder Engagement & Change Management

Present analytical insights and model outcomes in a clear, non‑technical manner to senior stakeholders in Risk, Compliance, and Business.
Collaborate with Operations, Technology, and Change teams to embed models into processes, controls, and decisioning systems.
Provide training and guidance to Risk and Compliance teams on the use and limitations of analytical models and AI tools.

Key stakeholders

Other Responsibilities

Exposure to advanced machine learning methodologies is a plus
Embed “Here for Good” and Group values within the team and across partner interactions.
- Perform other responsibilities as assigned under Group, country, business, or functional policies and procedures, consistent with role scope.