Department Overview:
The Intl AI CoE plays a key role in defining and implementing the firm's AI strategy, driving change through these capabilities, enforcing data, cloud and AI governance for the firm, and elevating Nomura's data culture.
Role Description:
- Information delivery & analytics. Deep expertise in data science with cutting-edge generative AI technologies to develop, implement, and optimize AI systems that create meaningful business value. You will work at the intersection of research and application, turning complex data into intelligent generative solutions.
- Model Development & Research. Design and develop generative AI models for various applications (text, image, code, multimodal). Research and implement novel approaches in prompt engineering, RAG systems, and model alignment. Stay current with latest research in generative AI, LLMs, and related fields
- Applied AI Solutions. Translate business requirements into generative AI technical solutions. Build and optimize retrieval-augmented generation (RAG) systems. Develop custom evaluation metrics for domain-specific generative tasks
- Be a trusted partner. Shape the information & analytics agenda at Nomura, and work with all of Nomura’s businesses in laying out their information & analytics adoption roadmaps.
- Risk Mindset: Familiar with risk and controls frameworks and ability to operate with a control mindset
Skills, experience, qualifications, and knowledge required:
Core Skills requirement:
- Proven experience developing and fine-tuning models using LLMs, diffusion models, and transformer architectures. Proficiency with frameworks such as Hugging Face, LangChain, or LlamaIndex. Working knowledge of Python libraries including pandas, NumPy, and scikit-learn for data analysis and model development.
- Demonstrated understanding of generative AI techniques, including attention mechanisms, tokenization, and embeddings. Hands-on experience applying prompt engineering, few-shot, and in-context learning for AI applications. Experience with model evaluation for generative performance, and working knowledge of responsible AI, bias mitigation, and safety frameworks. Familiarity with vector databases and semantic search systems.
- Proficiency in programming languages such as Python, SQL, and Unix shell scripting for AI and data engineering workflows.
- Experience designing, building, and deploying scalable and resilient microservices, including the development of efficient and secure server-side APIs.
- Proven experience implementing CI/CD pipelines (e.g., Jenkins, GitLab) and applying DevOps methodologies to automate deployment and integration processes.
- Experience with cloud technologies such as AWS EC2, EMR or similar tools with ability to drive design and data model discussions, hybrid data architecture.
- Experience collaborating with cross-functional and geographically dispersed teams across multiple regions to deliver AI/technology solutions.
- Proven ability to manage concurrent AI projects and meet delivery timelines in dynamic and fast-changing environments.
- Experience managing stakeholder expectations of senior management.
- Proficiency in written and verbal communication skills, with the ability to document AI processes and present technical content clearly to both technical and non-technical audiences.
- Demonstrated analytical and problem-solving skills with experience deriving data-driven insights and actionable recommendations.
- Experience evaluating business or technical requirements, identifying improvement opportunities, and proposing solutions that enhance system or business value.
Education and experience:
- At least 4-year Bachelor’s degree in quantitative fields with minimum of 5 years of relevant data experience in data scientist /Gen AI, preferably in financial organizations or Masters in quantitative fields (Computer Science, Statistics or similar)
- Experience of working with a multi-cultural, multi-disciplined, globally dispersed teams
- Professional certifications in AI/ML frameworks, cloud technologies, or DevOps tools (e.g., AWS Certified Machine Learning, TensorFlow, or Kubernetes) are advantageous.
Nomura Competencies
Explore Insights & Vision
- Identify the underlying causes of problems faced by you or your team and define a clear vision and direction for the future.
Making Strategic Decisions
- Evaluate all the options for resolving the problems and effectively prioritize actions or recommendations.
Inspire Entrepreneurship in People
- Inspire team members through effective communication of ideas and motivate them to actively enhance productivity.
Elevate Organizational Capability
- Engage proactively in professional development and enhance team productivity through the promotion of knowledge sharing.
Inclusion
- Respect DEI, foster a culture of psychological safety in the workplace and cultivate a "Risk Culture" (Challenge, Escalate and Respect).
Diversity Statement
Nomura is committed to an employment policy of equal opportunities and is fundamentally opposed to any less favourable treatment accorded to existing or potential members of staff on the grounds of race, creed, colour, nationality, disability, marital status, pregnancy, gender, or sexual orientation.
DISCLAIMER: This Job Description is for reference only, and whilst this is intended to be an accurate reflection of the current job, it is not necessarily an exhaustive list of all responsibilities, duties, skills, efforts, requirements or working conditions associated with the job. The management reserves the right to revise the job and may, at his or her discretion, assign or reassign duties and responsibilities to this job at any time.
Nomura is an Equal Opportunity Employer
SFID: 12416
