You are a strategic thinker passionate about driving solutions in Business Analysis, Reporting and Analytics, and Fraud and Anomaly Detection. You have found the right team.
As a Business Analysis Associate I within our Corporate Investment Banking Payments Operations team, you will be responsible for improving operational efficiency, advancing strategic initiatives, and enabling service excellence through data-driven insights, automation, and strong cross-functional partnership. You will lead the Reporting and Analytics portfolio for fraud and anomaly detection across payments operations, delivering executive-ready reporting, dashboards, and ROI-driven business cases. You will analyze complex datasets and partner with Technology and Operations to deploy models and automation, strengthen controls, and improve risk outcomes and operational efficiency.
Job Responsibilities
- Oversee end-to-end delivery for the Reporting and Analytics portfolio focused on fraud and anomaly detection across payments, reconciliations, and exceptions.
- Deliver ad-hoc and recurring reporting and produce executive-ready materials that quantify impact and performance.
- Prepare status updates, proposals, and business cases for senior leadership, articulating ROI from detection and automation initiatives.
- Analyze complex transaction and operations datasets using advanced analytics to identify patterns, outliers, and typologies and to test actionable hypotheses.
- Develop and apply statistical and machine learning models for classification, time series, and anomaly detection, communicating assumptions and outcomes to stakeholders.
- Collaborate with Technology and Operations to translate requirements into deployable capabilities, including testing, calibration, and case-management integration.
- Strengthen risk mitigation through root-cause analysis, continuous improvement, data quality controls, drift monitoring, and detection governance.
- Automate data ingestion, transformation, scoring, and alert routing by replacing manual workflows with reusable, well-tested scripts and jobs.
- Recommend prioritized insights and action plans, aligning cross-team deliverables and dependencies to achieve defined KPIs and outcomes.
- Build dashboards and visualizations that track risk and operational performance, enabling stakeholder transparency and self-service analytics.
- Coach and delegate tasks to support team capability-building, consistent execution, and a culture of continuous learning.
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Required qualifications, capabilities and skills
- 4+ years of experience analyzing complex datasets and translating insights into business outcomes with strong stakeholder communication.
- Strong statistical foundation (hypothesis testing, probability, sampling, regression) and experience with imbalanced/noisy datasets.
- Proficiency in SQL, including complex joins, window functions, and performance tuning on large datasets.
- Hands-on proficiency in Python (e.g., pandas, numpy, scikit-learn) or equivalent for data preparation, modeling, and automation.
- Experience building and evaluating detection analytics (rules and ML), including feature engineering, tuning, thresholding, and metrics (precision/recall, ROC/PR AUC, F1).
- Ability to explain model decisions to non-technical audiences; familiarity with explainability and model governance concepts.
- Advanced Microsoft Excel (pivot tables, lookups, VBA/macros) and strong PowerPoint skills; working knowledge of Visio and Word.
- Understanding of business process analysis/modeling and the software delivery lifecycle (requirements, testing, deployment, change management).
- Experience working with large, multi-source datasets and designing reproducible, version-controlled workflows.
Preferred qualifications, capabilities and skills
