PulliContract Type Permanent /li /ul h3Job Description /h3 pUnion Bancaire Privée (UBP) is a leading Private Bank specializing in Wealth Management (WM), offering tailored financial solutions to a diverse international clientele. Data analytics plays a key role in strengthening operational oversight, improving client understanding, and enhancing compliance and risk management processes. /p pAs a WM Data Scientist within the COO Wealth Management office, you will work at the intersection of data science, WM operational processes, and compliance analytics. The role focuses on analyzing internal data to identify patterns in client activity, operational workflows, and risk indicators, helping the organization better detect anomalies, improve client monitoring frameworks, and strengthen decision‑making. /p pThis position goes beyond traditional reporting. You will apply statistical methods, behavioral analytics, and quantitative modelling to improve rule‑based monitoring frameworks, support client lifecycle analytics, and optimize operational risk controls. /p pThe role also includes contributing to the definition of analytical frameworks and data specifications that will support future AI initiatives within the Wealth Management COO organization. /p h3Mission /h3 pDevelopment of intelligent analytical solutions to complex operational and risk‑related problems by extracting, transforming, modelling, and analysing data across multiple banking systems. /p pThe role focuses particularly on analytical challenges at the intersection of WM operations, compliance monitoring, and business risk controls, including the optimisation of monitoring alerts and detection frameworks. /p pYou will be mentored by the Head of WM Reporting Dashboards located in our Zurich office, with occasional travel to Geneva. /p h3Main responsibilities /h3 ul liExtract, transform, and structure data from multiple internal banking systems and operational processes /li liPerform advanced statistical analysis and data exploration to identify behavioural patterns in client activity and operational processes /li liAnalyse and refine rule‑based monitoring scenarios and threshold parameters used in transaction monitoring frameworks /li liDevelop quantitative models and analytical approaches to improve client segmentation, lifecycle analysis, and risk indicators /li liContribute to the optimisation of monitoring alerts and detection frameworks related to client activity and transaction behaviour /li liTranslate analytical findings into clear insights and recommendations for operational, compliance, and management stakeholders /li liContribute to defining analytical specifications and data frameworks supporting future advanced analytics and AI initiatives /li /ul h3Qualifications /h3 ul liAcademic degree (BA/MA) in Mathematics, Statistics, Computer Science, Data Science, or a related field /li liAt least 5 yearsof experience in asimilar role /li liBanking experiencestrongly preferred, or experience in asimilar data science environment /li liInternational work experiencedesired for this role /li liFluent in English; additional languages are an advantage /li liExperience working with large datasets and applying statistical or quantitative methods to operational, compliance, or risk‑related problems /li liExperience analysing rule‑based monitoring frameworks, risk indicators, or behavioural patterns in financial data is highly valued /li liStrong technical skills in SQL and Python /li liExperience with data visualisation or business intelligence tools (e.g. Power BI) is beneficial but not the primary focus of the role /li liExposure to transaction monitoring, KYT/KYC processes, or compliance analytics is a must /li liStrong analytical and curious mind with excellent research, communication, and presentation skills /li liSelf‑discipline, quality conscious and goal‑oriented approach and readiness for an agile working environment /li /ul bCandidates must have the legal right to work in Switzerland at the time of hire. This position is 100% on‑site in Zurich, Switzerland. /b /p #J-18808-Ljbffr