Data Analyst

Responsibilities
• Develop and maintain systems in accordance with department standards and conduct system analysis tasks
• Provide support for Risk Data reporting and analysis.
• Create and update documentation for systems.
• Build analytical and scientific solutions to address business issues
• Support data democratization within the company by developing dashboards and transferring skills.
• Support the implementation of various metadata applications in a Cloud platform.
• Collaborate with software developers and machine learning engineers to implement analytical models into production.
• Utilize EWM for version control and project management, collaborating with data scientists and engineers.
• Create Confluence pages, data dictionaries, and metadata for technical documentation.
• Utilize data visualizations to present findings and insights relevant to risk control.
• Collaborate with Operations staff to ensure the quality and availability of production application systems.

Requirements
• Degree holder in Computer Science, Data Analytics/ Science, Information Management or a related field.
• At least 5 years of experience in data analytics and/or related industries, with at least 2-3 years in data science/cloud platform.
• Familiarity with common data science languages/toolkits, such as Python, SQL, R, Scala, Apache Spark, Keras, etc., for data manipulation and deriving insights from large datasets is desirable.
• Possess solid experience in Unix scripting and SQL/PLSQL programming in Oracle DB.
• Possess solid experience in key machine learning and big data cloud platforms, such as Microsoft Azure ML Services & Data Warehouse, AWS SageMaker & Redshift, Google ML and BigQuery, etc.
• Experience with data architectures and data visualization BI tools (e.g., Tableau, PowerBI, Cognos, etc.).
• Experience working with large-scale datasets and complex data models.
• Good to have exposure to Bank Risk Management and Data Warehouse
• Strong communication and presentation skills to effectively convey findings to both technical and non-technical stakeholders.
• Ability to work independently with minimal supervision and collaboratively in a team.
• Self-motivated, proactive, and capable of multitasking.