Data Science & AI | Singapore, SG | Flexible

Robert Walters; Singapore; Hybrid; SGD 70,000 - 100,000; Full time

Job summary

A leading company in Singapore seeks a Data Science & AI expert to drive analytics and AI strategies. You will ensure data quality and governance, manage data architecture solutions, and work closely with various business units. Candidates should possess a strong quantitative background and relevant experience in financial organizations.

Qualifications

• Experienced in data engineering / MLOps with at least 5 years in related roles.
• Proficiency in programming languages is essential.
• Educational background in quantitative fields is preferred.

Responsibilities

• Responsible for data management and analytics delivery.
• Integrate, deploy and monitor AI/ML products and solutions.
• Collaborate across multidisciplinary global teams.

Skills

Data management

Microservices Development

Programming languages (Python, SQL, Java)

Communication skills

Teamwork in cross-cultural environments

Analytical skills

Education

Bachelor’s degree in quantitative fields

Tools

CI/CD, Jenkins, Ansible

Cloud technologies (EC2, EMR, Snowflake)

ETL tools

Orchestration tools (Airflow, Autosys)

React (UI development)

Job description

Data Science & AI

Robert Walters Singapore Apply now Posted 1 day ago Flexible Job Permanent Competitive

Data Science & AI

Robert Walters Singapore Apply now

The Chief Data Office plays a key role in defining and implementing the firm's data, cloud and AI strategy, driving change through these capabilities, enforcing data, cloud and AI governance for the firm, and elevating Organization's data culture. Governance remains a critical focus area, and the Chief 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:

• 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. Enabling data architecture and delivery of data-analytics platforms and Solutions- on-premises, cloud, and hybrid ensuring adherence and conformance to organization standards and policies
• Be a trusted partner. Shapethe information & analytics agenda at organization, and work with all of Organization’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:

• 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, SQL, Java, Unix scripting etc.) and with orchestration tools like Airflow or Autosys
• Experience with cloud technologies such as EC2, EMR, Snowflake or similar tools with ability to drive design and data model discussions, hybrid data architecture.
• Proficiency in React with hands-on experience in UI development a plus.
• 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

• At least 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 or Masters in quantitative fields (Computer Science, Statistics or similar)
• Experience of working with a multi-cultural, multi-disciplined, globally dispersed teams
• Certifications in relevant technologies or frameworks are a plus.

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