Vice President - AI Data Scientist - Group Technology

NOMURA SINGAPORE LIMITED; Singapore; On-site; SGD 120,000 - 150,000; Full time

Job summary

A leading financial services firm in Singapore seeks an experienced Data Scientist to define and execute AI strategy, leading a team to innovate and implement data-driven solutions. The ideal candidate will have extensive experience with generative AI technologies, proven leadership skills, and a strong foundation in programming and data science methodologies. This role offers a unique opportunity to shape the firm's AI landscape while collaborating across functions.

Qualifications

• At least 10 years of relevant experience in data science or AI.
• Proven experience in team leadership and mentorship.
• Experience designing and deploying microservices.

Responsibilities

• Define data science strategy and lead advanced analytics.
• Build and mentor a team of data scientists.
• Translate business requirements into generative AI solutions.

Skills

Developing and fine-tuning models using LLMs

Proficiency with frameworks like Hugging Face

Proficiency in Python, SQL, Unix shell scripting

Experience with cloud technologies

Strong analytical and problem-solving skills

Education

Bachelor’s degree in quantitative fields

Tools

AWS EC2

Jenkins

TensorFlow

Job description

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:

• Scientific Leadership. Define data science strategy and research agenda aligned with business objectives. Lead advanced analytics and AI model development across multiple domains. Establish scientific standards, methodologies, and best practices for the team. Drive innovation through experimentation with cutting‑edge AI techniques. Publish research findings and represent the company at industry conferences. Evaluate and adopt emerging AI technologies and methodologies
• Team Leadership & Development. Build, lead, and mentor a team of data scientists. Provide technical guidance on complex modeling challenges and research directions. Conduct performance evaluations and create individual development plans
• Information delivery & analytics. Deep expertise in data science with cutting‑edge generative AI technologies to develop, implement, and optimise 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 optimise 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, tokenisation, 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 10 years of relevant data experience in data scientist /Gen AI, preferably in financial organisations 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: 11826