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Urgent! Data Analyst - Corporate Banking Job Opening In Singapore, Singapore – Now Hiring Radiant Digital
We are seeking a highly analytical and detail-oriented Data Analyst to be part of us.
The role will focus on analyzing large datasets, generating actionable insights, and supporting strategic decision-making.
The ideal candidate will have strong data management skills, financial domain knowledge (Preferably Regulatory Reporting, Risk and Compliance in a corporate banking products), and the ability to communicate findings in a clear, business-oriented manner.
Recruitment Professional | Expert in Sourcing and Hiring Top Talent | Specializing in Tech & Engineering Roles
Key Responsibilities
Collect, clean, and validate data from multiple banking systems (e.g., loan management, treasury, trade finance, payments).
Perform quantitative and qualitative analysis on corporate banking portfolios, including lending, deposits, trade finance, and treasury products.
Work with stakeholders to identify business needs and translate them into data-driven solutions.
Conduct trend, variance, and scenario analysis to support pricing, profitability, and client segmentation.
Ensure compliance with data governance, quality, and regulatory reporting standards.
Partner with technology teams to improve data pipelines, automate reporting, and implement advanced analytics use cases.
Required Skills & Qualifications
Bachelor’s degree in data science, Statistics, Economics, Finance, Computer Science, or a related field.
Minimum 2–5 years of experience as a Data Analyst, ideally within banking or financial services.
Familiarity with statistical analysis tools (Python, R) preferred.
Good understanding of corporate banking products (loans, deposits, trade finance, treasury, payments).
Knowledge of risk, compliance, and regulatory reporting frameworks in banking.
Strong analytical, problem-solving, and critical-thinking skills.
Excellent communication skills to translate technical data into business insights.
Preferred Attributes
Experience in data warehousing, ETL, or big data platforms (Ex: Snowflake, Hadoop, Spark).
Exposure to machine learning techniques for credit/risk scoring or client segmentation.
Strong business acumen with an ability to connect data insights to revenue, cost, and risk drivers.
Ability to work in cross-functional teams within a fast-paced banking environment.
Regulatory scope (for alignment):
• Liquidity – MAS Notice 649 (MLA & LCR), MAS Notice 652 (NSFR), MAS Notice 640 (Asset Maintenance for foreign bank branches).
1) Track Checklists (Prepare before workshop)
A.
Finance – Regulatory Reporting & Controls
Reconciliations: GLMAS (balances, P&L impacts), period-over-period variances, thresholds & narrative packs.
Liquidity mechanics: LCR/MLA steps (HQLA sourcing, runoff/inflow rates, intragroup), NSFR scope confirmation (ASF/RSF mapping).
Large exposures & asset maintenance (branch): aggregation logic, connected parties, qualifying asset inventory & ratio.
Finance deliverables: As-is process map & RACI; GLMAS reconciliation policy & variance playbook; DQ rules for high-risk fields; submission calendar & signer matrix.
Credit data to MAS: staging/NPA/forbearance flags, PD/LGD/EAD, collateral haircuts & cadence; industry/country tags; off-BS exposures.
Concentration & LE: counterparty hierarchy/LEI mapping; related-party detection; intragroup aggregation.
Market/Treasury interfaces: trading/banking book positions, HQLA eligibility & encumbrance tracking (align to 649).
Liquidity assumptions: LCR runoff factors, inflow caps, operational deposits; NSFR ASF/RSF mapping library.
Stress testing/IWST: scenario data pulls, ownership, documentation for MAS Q&A; traceability to reported numbers.
Operational risk: incident thresholds for MAS notification; KRI linkage where reportable.
Risk deliverables: Risk data dictionary & lineage (source→ MAS field); LE aggregation spec; Liquidity Assumptions Register (owners/approvals); Stress-test data pack template.
Applicability matrix: Branch obligations across 610/1003, 649/652, 640; disclosures alignment with HO where relevant.
Reg change mgmt.: horizon scanning, impact assessment, vendor rule-pack uptake, SOP & training updates.
Submission governance: maker-checker, manual-adjustment policy, late-change protocol, retention.
Issue mgmt.: MAS Q&A playbook, resubmission controls, corrective action tracking.
Assurance: control testing plan, Internal Audit alignment, inspection readiness (“brown envelope” kit).
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Analyst
Industries
IT Services and IT Consulting, Banking, and Investment Banking
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Unlock Your Data Analyst Potential: Insight & Career Growth Guide
Real-time Data Analyst Jobs Trends in Singapore, Singapore (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Data Analyst in Singapore, Singapore using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 11065 jobs in Singapore and 10086 jobs in Singapore. This comprehensive analysis highlights market share and opportunities for professionals in Data Analyst roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Radiant Digital is currently hiring and seeking a Data Analyst Corporate Banking to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Radiant Digital adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Data Analyst Corporate Banking Jobs Singapore varies, but the pay scale is rated "Standard" in Singapore. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Data Analyst Corporate Banking typically include Other General and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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Before the Interview:To prepare for your Data Analyst Corporate Banking interview at Radiant Digital, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Radiant Digital's products or services and be prepared to discuss how you can contribute to their success.
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