
Risk Services - Digital Solutions Risk AI Services Associate - 2026 Intake
- Singapore
- Permanent
- Full-time
- Foundational Knowledge of Technology: Demonstrates a foundational knowledge of technology concepts and applications and how they can be applied to solve real-world problems.
- Problem Solving and Analytical Skills: Utilize analytical skills to tackle complex business challenges, interpret data, and offer strategic recommendations that drive informed decisions.
- Client Relationship Management: Build and maintain strong, trusted relationships with clients, acting as a trusted advisor by demonstrating a deep understanding of client needs.
- Team Collaboration: Collaborate effectively within diverse teams and with external stakeholders.
- Communication Skills: Demonstrate clear and persuasive communication, articulating ideas and insights effectively to ensure understanding by clients and team members.
- Professionalism and Integrity: Uphold high standards of professional conduct and demonstrate integrity in all interactions.
- Continuous Learning and Adaptability: Embrace a growth mindset and demonstrate a commitment to continuous learning.
- Foundational Cloud Platforms Proficiency: Demonstrates knowledge and practical experience with foundational platforms like AWS, Azure, and GCP.
- Programming Skills: Possesses a solid understanding of programming, with practical experience in SQL, Python, and R.
- Data Visualisation Skills: Possesses foundational knowledge in data storytelling and visualization using tools like Power BI and Tableau.
- Requirement Translation and Technical Logic Design: Translate client needs into actionable technical solutions, bridging business challenges with structured technical implementation.
- Data: Demonstrates a foundational understanding of data structures, database systems, and data processing techniques. Desired skills include:
- Database, Datawarehouse and Data lake management and tools such as: SSMS, PostgreSQL, Snowflake, Databricks, Elasticsearch, Neo4J and MongoDB.
- Data architecture design and assessment (e.g. patterns to handle batch ingestion, near-real-time ingestion, event streaming, Pub/Sub models)
- Data modelling techniques for dimensional data models and conceptual-logical-physical models
- Data integration and management, through usage of ETL and API management tools such as: Informatica, AWS Glue, Apigee, MuleSoft, AWS API Gateway and Postman.
- Data quality and data governance concepts, and tools such as: Informatica Data Quality, SAP Data Quality Management, Collibra, Alation, Purview and Informatica.
- AI: Possesses knowledge and practical experience applying Automation, Analytics, AI and GenAI to solve business problems. Desired skills include:
- Experience and enthusiasm designing and executing projects that leverage Automation, Analytics, AI and GenAI to resolve business challenges
- Conceptual understanding of AI concepts (e.g., tree-based models, transformers etc), ability to explain such concepts to business stakeholders and translate them into business impacts
- Awareness of evolving technologies and methodologies in AI and familiarity with modern data science development tools
- Ability to identify a variety of risks (ethical, model etc) posed by the usage of AI systems