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Company Overview
A leading global financial institution is advancing its Corporate and Investment Banking (CIB) division by integrating AI and data science capabilities across all business areas. The organization focuses on Financial Markets and Transaction Banking, aiming to deliver cutting-edge analytics, innovative AI solutions, and data-driven decision-making to clients worldwide.
Summary
The Director of Data Science & Innovation, CIB, will lead the development and deployment of AI and machine learning solutions across Corporate and Investment Banking. This role requires strong expertise in classical machine learning techniques as well as Large Language Models, with a focus on delivering practical, high-impact solutions while mentoring and upskilling junior team members.
Key Responsibilities
Liaise with product owners and business stakeholders to identify pain points, gather requirements, and define use-cases
Design, develop, and deploy AI/ML solutions in collaboration with product owners, MLOps engineers, and the wider Tech and Data teams
Productionize machine learning solutions and ensure they meet business and operational standards
Stay current with developments in Data Science and NLP and share best practices with the team
Mentor and upskill junior team members
Strategy
Develop data and AI solutions in alignment with business strategy, ensuring timely delivery, budget compliance, and high quality
Governance
Apply Data Quality Management Framework (DQMF) for analytics and AI projects
Adhere to risk, audit, and regulatory requirements, including monitoring and remediating issues identified in audits
Incorporate regulatory requirements into platform design
Regulatory and Business Conduct
Exhibit exemplary conduct aligned with the Group’s Values and Code of Conduct
Ensure compliance with all applicable laws, regulations, and the Group Code of Conduct
Proactively identify, escalate, mitigate, and resolve risk, conduct, and compliance issues
Key Stakeholders
Technology and Engineering teams across the bank
Corporate and Investment Banking (CIB) business teams
Digital, Data & Coverage Platforms (DDCP)
Qualifications
Degree in Computer Science, Software Engineering, IT, or related field
6+ years of experience in machine learning, data science, or other quantitative roles, preferably in banking, finance, fraud, or risk
Proficiency in Object-Oriented Programming (OOP) with Python
Strong expertise in machine learning, deep learning, and statistical analysis techniques
Experience with NLP/Document AI, entity matching, anomaly and fraud detection is advantageous
Proficient in ML, DL, and NLP libraries such as Scikit-learn, HuggingFace, LangChain, and PyTorch
Experience with big data tools such as Hadoop, Spark, and Hive in cloud environments
Familiarity with CI/CD and MLOps frameworks for end-to-end ML pipelines
Experience leading data science projects and mentoring junior resources
Experience working in agile environments
Excellent communication skills to convey complex technical concepts to non-technical stakeholders
Self-driven, highly motivated, and passionate about delivering high-quality client solutions
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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