Marcus Goldman Sachs, MI Manager, Savings Analytics & Forecasting, Associate
Job in
Birmingham, West Midlands, B1, England, UK
Listed on 2026-05-31
Listing for:
WeAreTechWomen
Full Time
position Listed on 2026-05-31
Job specializations:
-
IT/Tech
Data Analyst, Business Systems/ Tech Analyst, Data Warehousing, Data Engineer
Job Description & How to Apply Below
Your Impact
- Bring a customer-focused, decision-ready view of performance by delivering clear MI and forecasting that helps teams understand how customers are behaving (inflows, withdrawals, retention, maturities) and what actions to take next, aligned to the outcomes focus of Consumer Duty.
- Strengthen the bank’s ability to run smoothly day-to-day by providing timely, accurate, and well-explained reporting across Commercial, Products, Marketing, Customer & Telephony Operations, and Risk, enabling leaders to spot issues early, prioritise fixes, and track improvements.
- Improve process innovation and efficiency by reducing manual reporting effort through better BI-ready datasets, automation, and repeatable reporting routines, supported by robust data management practices.
- Reinforce risk management and control by ensuring MI and forecasting are well governed: consistent KPI definitions, reconciliation and data quality checks, controlled distribution, and audit-ready documentation; operating appropriately under UK GDPR.
- Support better pricing and planning decisions by providing scenario-based insights on how rate changes and market movements may affect savings balances and flows, and by applying proportionate model governance practices consistent with banking expectations.
- Savings Forecasting Support:
Deliver forward views of savings balances and flows (gross inflows, withdrawals, net flows, maturity roll-offs), segmented by product and cohort, using appropriate forecasting techniques. - Scenario & Sensitivity Analysis:
Provide scenarios to support planning and pricing (e.g., rate moves, competitor positioning, seasonal impacts), with clearly stated assumptions and limitations. - Model Governance (proportionate):
Apply proportionate documentation, monitoring, and controls for forecasting models in line with banking model risk management expectations.
- Cross-functional Collaboration:
Partner with Engineering, Data Platform, Product & Pricing, Treasury/ALM, Finance, Marketing, Operations, and Risk to align on data definitions, metrics, and delivery priorities. - Data Source Development:
Identify gaps in reporting and forecasting coverage; collaborate with stakeholders to onboard or develop new data sources needed for comprehensive MI and analytics. - Knowledge Sharing:
Maintain clear documentation and run‑book style materials to support transparency, continuity, and efficient onboarding for analysts and stakeholders.
- Reporting Delivery:
Develop, maintain, and enhance MI packs, dashboards, and recurring performance views for various forums ensuring clear commentary and "so what" insights. - Release Management:
Manage the release lifecycle for dashboards and reports (testing, stakeholder sign‑off, timely deployment), with clear change notes and version control. - Method Consistency:
Ensure consistent application of definitions, reporting methodologies, and segmentation logic across divisions and channels.
- Data Stewardship:
Act as a data steward for savings MI domains, ensuring data is accurate, consistent, reconciled, and fit for purpose across source systems and reporting tools. - Data Governance & Controls:
Implement and uphold governance practices covering KPI definitions, data quality standards, access controls, and controlled MI distribution, aligned to UK GDPR expectations. - Auditability:
Maintain an audit‑ready trail of metric definitions, data lineage, key controls, and changes to critical reporting outputs.
- Data Management (ETL/ELT):
Support end-to-end management of reporting datasets, including extraction, transformation, and loading into BI tools, ensuring integrity, availability, and refresh reliability. - BI-ready Data Products:
Shape and refine curated datasets (clean, well-structured, documented) that can be reused across MI, forecasting, and pricing analytics. - Monitoring & Troubleshooting:
Monitor pipelines and reporting solutions for performance issues, investigate discrepancies, and…
Position Requirements
10+ Years
work experience
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