Data Analyst – Corporate Banking

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.Key ResponsibilitiesCollect, 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 & QualificationsBachelor’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 AttributesExperience 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):• MAS 610 / Notice 1003 reporting (granular data & taxonomy; DCG submissions). • Liquidity – MAS Notice 649 (MLA & LCR), MAS Notice 652 (NSFR), MAS Notice 640 (Asset Maintenance for foreign bank branches). • Submission channel – MAS Data Collection Gateway (DCG) via MASNET (XML/XLS payloads, validations, due-date alerts). 1) Track Checklists (Prepare before workshop)A. Finance – Regulatory Reporting & ControlsProduction flow: Source → Staging → Reg Data Mart → Transform/Rules → XML/XLS → DCG; list all manual touchpoints & key-person risks. Reconciliations: GL↔️MAS (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. DQF: critical fields (industry/country/collateral/credit quality), preventive vs detective controls, exception dashboards.Toolchain: current platform coverage (templates/rule packs), spreadsheet/Alteryx governance, audit trail.Cut-over calendar: Day-X timings, sign-off chain, resubmission protocol (DCG). Finance deliverables: As-is process map & RACI; GL↔️MAS reconciliation policy & variance playbook; DQ rules for high-risk fields; submission calendar & signer matrix.B. Risk – Credit • Market • Liquidity • OperationalCredit 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.C. Compliance – Reg Change • Governance • AssuranceApplicability 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).Compliance deliverables: Obligations register (owners/due dates); Reg-change SOP; Controls inventory (design + OET schedule); MAS correspondence log & RACI.