{"id":2545774,"url":"https://alion.io/job/ubp-wealth-management-ai-data-scientist-engineer","title":"Wealth Management - AI Data Scientist / Engineer","company":{"id":451139,"name":"UBP","domain":"ubp.com","url":"https://alion.io/company/ubp-2","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":13,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Zurich, Switzerland"],"countries":["CH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Function Calling","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-10-14T13:37:18Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T11:56:10Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Union Bancaire Privée (UBP) is a leading Private Bank specialising in Wealth Management (WM), serving a sophisticated international client base. Within the WM Client Lifecycle AI & Reporting Team, we are building practical AI solutions that improve how Wealth Management teams work across the client lifecycle - from onboarding and periodic review to KYC, transaction alert handling, to client intelligence.\nWe are looking for an WM AI Data Scientist / Engineer who enjoys turning difficult business problems into working technology.\nThis is not a traditional reporting role, and it is not a pure research position. We are looking for someone who can take an idea, challenge it, shape the solution and then build it.\nYou will work across AI, software engineering, data and business processes, developing tools that combine Large Language Models, APIs, structured and unstructured data, backend services and user-facing applications. Additionally, the role offers opportunities to contribute to client onboarding, periodic review, KYC/KYT, transaction monitoring, document understanding and banker productivity.\nThe right candidate will be comfortable moving from a conversation with a business stakeholder to a technical architecture, from a rough prototype to a usable application, and from experimentation to something that can operate reliably in a regulated banking environment.\nYou will work closely with the Head of WM Client Lifecycle AI & Reporting in Zurich, with occasional travel to Geneva.\nMain responsibilities\nTurn ambiguous business problems into clear technical solutions;\nDesign and build AI-enabled applications from concept through to implementation;\nIntegrate Large Language Models into real business workflows using techniques such as RAG, structured prompting, tool use and agentic workflows;\nBuild backend services and APIs that connect AI applications with internal systems, data sources and business processes;\nDevelop or contribute to user-facing web applications that make AI capabilities simple and intuitive to use;\nWork with structured and unstructured information, including documents, free text, client data and workflow data;\nBuild data-processing pipelines that prepare and organise information for AI applications;\nTest solutions with real users, challenge assumptions and improve applications based on feedback;\nBuild solutions that are traceable, maintainable and appropriate for a regulated environment;\nTake end-to-end ownership of technical delivery rather than focusing on a single narrow component;\nExplain technical choices, limitations and risks clearly to non-technical stakeholders;\nRequirements\nAcademic degree (BA/MA) in Computer Science, Artificial Intelligence, Software Engineering or a closely related technical discipline;\nAt least 3+ years of relevant professional experience in AI engineering, software engineering or applied AI development;\nProven experience building real applications, products or production-quality prototypes;\nHands-on experience integrating LLMs or Generative AI into applications;\nExperience developing backend services and working with modern application architectures;\nExperience developing web-based user interfaces is a strong plus;\nFamiliarity with RAG, vector databases, knowledge graphs, graph databases or semantic search is an advantage;\nExperience with client due diligence, client lifecycle processes or document-heavy workflows is beneficial;\nAbility to translate business problems into technical solutions, with sound product thinking and an understanding of technical architecture and implementation;\nFluency in English; French or German is an advantage;\nStrong analytical and problem-solving skills, intellectual curiosity, and excellent research, communication and presentation skills;\nCandidates must have the legal right to work in Switzerland at the time of hire. 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