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Urgent! Data Analyst - Corporate Banking Job Opening In Singapore, Singapore – Now Hiring Radiant Digital

Data Analyst Corporate Banking



Job description

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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Required Skill Profession

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