Data Risk Analyst

Trust is the first of a new breed of banks in Singapore - digitally native and focused on delivering a delightful customer experience. You will work in a fast-paced and collaborative environment to solve new and interesting challenges each day. Together with our Trust team, you will help shape the future of our bank. As a **Data Risk Analyst** you'd be able to work on and solve many interesting challenges which we are facing, learn new ways of working, and help build delightful high quality products for our customers. You should be highly analytical with a diverse flair for risk and control, analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. Preferably, you have some Retail Consumer or Technology domain knowledge and audit experience. You are also familiar with the agile practices and working in sprints with other stakeholders such as the other Internal Audit team members, technology, business, and the data team to develop use cases for audit and identify emerging and thematic risks. You are comfortable working in a fast-paced environment with a high degree of ambiguity, get excited by solving complex problems and are happy to roll your sleeves up and get things done. As a digital bank and growing venture, the role offers a rare opportunity to partner across all business units to define innovative and automated audit approaches. This is a unique, challenging opportunity to be part of an end-to-end process to build a strong Internal Audit function within the new digital bank. **The Role Responsibility**: - Contribute to, and support the implementation of the data strategy and roadmap for the Internal Audit function. - Utilize data analytics in audits and continuous monitoring to identify and/ or escalate risks - Support the development of risk and control BI dashboards and automated monitoring on risks and controls. - Work with Internal Audit, technology, and data teams to leverage/ develop processes, tools, and capabilities for audit use cases. - Utilize predictive modelling to identify emerging risks or control issues. - Identify and map valuable data sources that are relevant to key business processes/ controls/ key risk indicators and automate collection processes. - Support the development of the Internal Audit risk data warehouse. - Support the Internal Audit team in using data analytics to actively track and escalate, where appropriate, significant issues and audit findings that remain unresolved. - Maintain effective relationships with internal stakeholders to provide input / assistance on developing their audit approach as required. - Share knowledge, skills, and experience on analytics and/ or automation with team members. - To assist the Internal Audit team in ensuring accurate and timely management reporting is provided to the Management Team. - Supporting the Internal Audit team where directed, the planning, fieldwork, and reporting of Internal Audit engagements to deliver agreed assurance objectives to established standards and timelines. **Role Specific Technical Competencies**: Skill Target proficiency level BI / Visualization tools (eg. Tableau, PowerBI) Core SQL Core Python/ R Core Machine Learning techniques (Supervised/ Unsupervised/ NLP) Entry Data Engineering Entry Project Management Entry - 2-4 years' work experience in data analytics, especially useful if in a Risk function or Banking industry. - Enjoys working in a dynamic environment, is passionate about risk, data and technology and can focus on key issues and the details that come with it. - Team player with the ability to collaborate and influence while maintaining independence and effective challenge of 1st and 2nd line. - Able to translate user requirements to a working analytics product - Experience using data science related languages/ tools (Python, SQL, Spark, R, advanced Excel, etc) to manipulate data and draw insights from large and ad-hoc data sets. - Experience using business intelligence tools/ platforms (e.g. Tableau, DataRobot) - Experience with cloud technologies (AWS, S3, Lambda, Sagemaker, EC2, etc) - Experience with a variety of machine learning techniques (supervised, unsupervised, anomaly detection, NLP) and understanding their real-world advantages / drawbacks. - Experience in Agile ways of working and familiarity with tools like Jira, Confluence, Trello, Slack etc. - Experience creating APIs - Ability to quickly learn new technologies/ products used by the Bank, leveraging it to extract data, or derive insights. - Objective-led approach with a problem-solving aptitude - Demonstrates ability to work independently and seek guidance when needed. - Demonstrates ability to multi-task without loss of quality. - Flexibility to work across different functions and situations and change priorities at short notice. - Demonstrates ability to think critically, objectively and "think outside the box" when analysing issues and recommending / de