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Specialist, Gen AI Solutions

Standard Chartered -
Bengaluru, Karnataka

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Job details

Permanent
5 days ago

Benefits

Health insurance
Paid sick time

Qualifications

CI/CD
Law
SAS
Big data
Software deployment
Spark
R
Master's degree
SQL
Analysis skills
Machine learning
Data management
Continuous integration
Risk management
Natural language processing
Agile
Portfolio management
Fraud prevention and detection
Data science
Solution architecture
AI
Communication skills
Python
Data Science
Analytics

Full job description

Requisition Number: 54414

Job Location: Bangalore, IND

Global Grade: Band 6

Work Type: Office Working

Employment Type: Permanent

Posting Start Date: 08/06/2026

Posting End Date: 30/06/2026

Job Summary

Drive the design, development, and deployment of advanced analytics, machine learning and AI solutions that strengthen the bank’s risk management and regulatory compliance capabilities by transforming traditional, reactive risk management into proactive, predictive, and automated frameworks.

The role sits within the AI CoE and partners with Risk, Compliance, Technology, and Data teams to:

Identify and prioritize high‑impact AI/ML use cases (e.g., financial crime, credit risk, operational risk, conduct & compliance monitoring).
Build robust, explainable models and analytical solutions that comply with internal policies and external regulations.
Embed models into business processes, ensuring they are trusted, monitored, and continuously improved.

Key Responsibilities

Strategy

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.

Business

Identify opportunities to enhance automation and alert quality (reducing false positives/negatives).

Key Responsibilities

Processes

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.
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.

People & Talent

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

Key Responsibilities

Risk Management

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

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

Reporting & Stakeholder Communication

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

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, Financial risk, Cyber Security, Model Risk, Operational Risk
Internal Audit / Assurance partners
COO / Finance partners (capacity and investment planning)
AI Solutions Team
Compliance & Governance

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

Technical & Operational Skills

Technical Skills

Strong hands‑on experience with advanced analytics and ML techniques, such as:

Supervised and unsupervised learning (classification, regression, clustering, anomaly detection)
Time series modelling and forecasting
Natural Language Processing (for compliance text analysis, document review, surveillance)

Proficiency in programming languages and tools commonly used for data science (e.g., Python, R, SQL; experience with Spark or similar big data tools is a plus).
Experience in model lifecycle management: development, validation, deployment, and monitoring.
Familiarity with MLOps concepts and tools (e.g., model versioning, CI/CD for ML, monitoring platforms) is desirable.
Solid understanding of data management practices, including data quality, lineage, and governance.

Skills and Experience

Risk & Compliance Knowledge

Practical experience in risk, financial crime, or compliance analytics within financial services or consulting is highly desirable.
Understanding of regulatory expectations related to model risk management, use of AI, and data privacy within banking.
Awareness of challenges such as bias, fairness, explainability, and ethical considerations in AI for risk and compliance.

Analytical & Problem-Solving Capabilities

Strong analytical thinking with the ability to decompose complex, ambiguous problems into structured analytical tasks.
Ability to balance technical sophistication with practical constraints (data quality, regulatory requirements, operational reality).
Skilled at quantifying benefit/risk trade‑offs and recommending pragmatic solutions.

Stakeholder & Communication Skills

Ability to communicate complex technical concepts in clear business language to non‑technical stakeholders.
Strong stakeholder management and influencing skills; able to collaborate effectively across Risk, Compliance, Technology, and Business.
Experience working in cross‑functional, agile or project‑based teams.

Personal Attributes

High integrity and strong risk and control mindset.
Curiosity and proactive learning attitude towards emerging AI, analytics, and regulatory trends.
Outcome‑oriented, with a focus on delivering value safely and compliantly.
Resilient, adaptable, and comfortable working in a fast‑evolving environment.

Qualifications

Education & Qualifications

Degree in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Engineering, or related discipline.
Postgraduate degree and/or relevant professional qualifications in analytics, risk, or compliance 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

Experience

Experience designing and delivering digital, data, or AI solutions in a complex, regulated environment (financial services or consulting preferred).
Hands‑on exposure to GenAI/LLM projects (POCs, pilots, or production solutions).
Background in one or more of: solution architecture, data/ML engineering, or advanced analytics

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.

Apply Now

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