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Company Overview
A leading global bank is driving innovation in Corporate and Investment Banking (CIB) by integrating advanced AI and data science across its operations, including Financial Markets and Transaction Banking. The organization focuses on leveraging AI, machine learning, and analytics to enhance decision-making, operational efficiency, and client solutions while maintaining high standards of governance and regulatory compliance.
Summary
The Manager, Data Science and Innovation, will lead the development and deployment of AI and data science solutions, including machine learning models and Large Language Models, to solve business challenges across CIB. This role combines technical expertise, strategic insight, and strong stakeholder management to deliver innovative, high-quality solutions in collaboration with cross-functional teams.
Responsibilities
Liaise with product owners and business stakeholders to identify pain points, gather requirements, and define business use-cases
Develop AI/ML solutions for various business challenges in collaboration with product owners and the wider team
Productionize AI/ML solutions with MLOps Engineers and the Technology & Data teams
Stay updated with developments in Data Science, NLP, and AI, and share best practices across the team
Mentor and upskill junior team members
Support the development of data and AI solutions aligned to business strategy, delivered on time, within budget, and with high quality
Ensure data quality standards (DQMF) are applied in analytics and AI projects
Adhere to risk, audit, and regulatory requirements, proactively identifying and remediating issues
Display exemplary conduct and embed the highest standards of ethics, regulatory compliance, and business conduct
Key Stakeholders
Technology and Engineering teams across the bank
Corporate and Investment Banking (CIB) business teams
Digital Channels and Client Data Analytics (DCDA)
Financial Crime Surveillance Operations (FSCO) / Compliance teams
Qualifications
Degree in Computer Science, Software Engineering, IT, or related fields
2+ years of experience in machine learning, data science, or quantitative roles (banking/finance experience preferred but not mandatory)
Proficient in Python with Object-Oriented Programming (OOP) skills
Knowledge of machine learning, deep learning, and statistical analysis techniques
Experience in NLP, DocumentAI, Entity Matching, and Anomaly/Fraud detection is an advantage
Familiarity with ML, DL, and NLP libraries such as Scikit-learn, HuggingFace, LangChain, and PyTorch
Experience working in agile environments
Strong communication skills, able to convey complex technical concepts to non-technical stakeholders
Self-driven, motivated, with a strong sense of ownership and passion for delivering high-quality client solutions
Role Specific Technical Competencies
Data Science
Python
NLP
Deep Learning
Stakeholder Management
Disclaimer
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1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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