Company overview
Nomura is an Asia-based financial services group with an integrated global network spanning over 30 countries. By connecting markets East & West, Nomura services the needs of individuals, institutions, corporates and governments through its three business divisions: Retail, Asset Management, and Wholesale (Global Markets and Investment Banking). Founded in 1925, the firm is built on a tradition of disciplined entrepreneurship, serving clients with creative solutions and considered thought leadership. For further information about Nomura, visit www.nomura.com
Department overview:
The Chief Data Office plays a key role in defining and implementing the firm's data strategy, driving transformational change through data capabilities, enforcing data governance for both transformation benefit and regulatory compliance, and elevating Nomura's data culture. Governance remains a critical focus area, and the Group Data Office, in partnership with Business and Corporate functions, is responsible for ensuring that the firm's data assets are managed in line with the firm's data management framework, policy and standards.
Role Description
Job Responsibilities:
- Enabling data architecture and delivery of data-analytics platforms and Solutions – on-premises, cloud, and hybrid
- Information delivery & analytics. State-of-the-art expertise across, data/information preparation, data insight & visualization using BI (or similar tools), and advanced data prediction using AI, ML, DL, etc.
- AI/ML Ops. Responsible for integration, deployment and monitoring of AI/ML products and solutions,
- Data management. Demonstrate expertise in data management to ensure the analytics products are appropriate/ethical and well-controlled.
- 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.
Skills, experience, qualifications and knowledge required:
Core Skills requirement:
- Designing and developing scalable data pipelines to collect and process large volumes of data from multiple sources.
- Building physical data models and ETL processes to ensure data quality, integrity, and accessibility.
- Microservices Development: Building and maintaining highly scalable and fault tolerant microservice, including efficient server-side APIs.
- Deployment: Hands on with CI/CD, Jenkins, Ansible, DevOps process, Enterprise integration patterns.
- Hands-on with programming languages (Python, Java etc.) and with orchestration tools like Airflow
- Experience with cloud technologies such as EC2, EMR, Snowflake or similar tools with ability to drive design and data model discussions, hybrid data architecture.
- Proficient in REST services, JSON data, Python 3, Linux/Unix Shell Scripting
- Proficient in modern data management methodologies and architecture e.g.- building data products and implementation of data mesh
- Experience with machine learning libraries and frameworks like LangChain, TruLens, MLFlow, TensorFlow, Scikit-learn, or PyTorch
- Deploying machine learning models into production environments and monitoring their performance over time.
- Collecting, cleaning, and analyzing large datasets to train and evaluate machine learning models.
- Ability to understand and integrate cultural differences and work effectively with virtual cross-cultural, cross-border teams.
- Flexibility to adjust to multiple demands, shifting priorities, ambiguity, and rapid change.
- Experience with senior stakeholder management will be an added advantage.
- Excellent communication (verbal, written, listening), presentation, and interpersonal skills.
- Able to analyze complex situations and derive workable actions.
- Able to constructively challenge requirements and current state to increase overall value to the firm.
Education and experience
Wide variety of degrees will be considered, however work experience will be of equal, if not greater importance
- Masters in quantitative fields (Computer Science, Statistics or similar) or at least a 4-year Bachelor’s degree in quantitative fields with minimum of 5 years of relevant data experience in data engineering / MLOps, full stack engineering, preferably in financial organizations
- Experience of working with a multi-cultural, multi-disciplined, globally dispersed teams
- Certifications in relevant technologies or frameworks are a plus.
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: 8877
