Current role
UBS · Associate Director
AI and data engineering initiatives, risk reporting, release oversight, governance and delivery leadership.
Zurich · Swiss citizen · Privacy-safe profile
AI, Data and Transformation Leadership in Swiss Banking
Senior AI and data leader with 15+ years across UBS, Credit Suisse and ETH Zurich, combining hands-on delivery with Agile leadership, stakeholder advisory and regulated-environment execution.
I help regulated organisations turn AI and data initiatives into practical business outcomes through production delivery, platform thinking, governance awareness and clear communication with senior stakeholders.
UBS Associate Director
Credit Suisse AVP
AI & Data Platforms
Risk & Governance
Agile Leadership
Leadership
Scrum Master · Agile Champion
Coaching teams, improving ways of working and supporting execution across multiple pods.
Platforms
Azure · Databricks · Foundry
Production data platforms and AI workflows in complex, regulated environments.
Foundation
ETH Zurich · Imperial
Research background in machine learning, strong technical communication and published work.
About
I work at the intersection of AI, data engineering and transformation in regulated banking environments. Over 15+ years across UBS, Credit Suisse and ETH Zurich, I have helped design and deliver production-grade data and AI solutions, from risk reporting platforms and GenAI-ready pipelines to country risk data products and stakeholder-facing dashboards.
My work combines hands-on delivery with business-facing leadership. At UBS, this has included leading data engineering initiatives, supporting a mission-critical risk management application, working within strict data governance, and serving as Scrum Master and Agile Champion across multiple pods. Earlier at Credit Suisse, I developed Palantir Foundry pipelines, gathered requirements, and showcased outcomes to stakeholders in risk-focused settings.
I bring a blend of technical depth, communication strength and practical execution. My background includes machine learning research at ETH Zurich, published work, and recent executive learning in AI strategy, generative AI and leadership, all of which support my focus on turning complex technology into measurable business outcomes.
Experience
A concise view of the roles and responsibilities most relevant to AI, data engineering, stakeholder-led delivery and transformation.
Jan 2024 – Present
UBS AG · Senior Data Engineer / Associate Director
- Direct strategic AI and data engineering initiatives within Group Operations and Technology.
- Lead development and production support of a mission-critical risk reporting application integrated into UBS systems.
- Built GenAI-ready data pipelines and MLOps workflows for internal knowledge and reporting use cases.
- Managed data access, security and compliance within highly restricted data environments.
- Served as Scrum Master for an 8-member team and Agile Champion across 7 pods.
Jun 2020 – Dec 2023
Credit Suisse AG · Big Data Developer / Assistant Vice President
- Developed big data solutions in risk-focused settings using Palantir Foundry and related tools.
- Led backend development and deployment of a country risk data pipeline.
- Led frontend development of dashboards to display key metrics and business insight.
- Gathered client requirements, showcased outcomes and managed stakeholder relationships.
- Worked with highly confidential banking data under strict access controls.
Nov 2018 – Feb 2020
UBS AG · Project Manager / Solution Developer
- Delivered automation and AI-related proof-of-concept work to improve business processes and reduce operational effort.
- Gathered and analysed engineering requirements with senior stakeholders.
- Contributed to Azure data lake implementation work linked to onboarding external AI research output.
- Helped steer fast-paced strategic projects with minimal supervision in multidisciplinary settings.
Research foundation
ETH Zurich and HES-SO Valais
- Conducted machine learning research in medical imaging, computer vision and applied analytics.
- Published and presented research in international journals, conferences and workshops.
- Built the technical depth and communication foundation that continues to shape later industry work.
Core strengths
AI and data platforms
- Python, PySpark, SQL and production-grade data engineering
- Azure, Databricks, Palantir Foundry and CI/CD workflows
- MLOps practices and platform-oriented delivery
- Governance-aware work in highly regulated environments
Transformation and leadership
- Agile leadership as Scrum Master and Agile Champion
- Stakeholder management across business and technology teams
- Requirements gathering, solution shaping and delivery coordination
- Clear communication with technical and non-technical audiences
Applied AI and research
- Generative AI, internal knowledge workflows and reporting automation
- Risk analytics, dashboards and insight delivery
- Machine learning research and scientific publication record
- Executive learning in AI strategy, leadership and communication
Python
PySpark
SQL
Azure
Databricks
Palantir Foundry
PowerBI
GitLab
JIRA
Confluence
Agile
Risk Platforms
Selected work
Representative themes drawn from recent roles and research. This section is intentionally concise and privacy-safe.
UBS
Risk reporting platform
Production delivery and release support for a central risk management application, with governance, deployment and operational reliability in focus.
UBS
GenAI-ready internal workflows
Data pipelines and MLOps workflows supporting internal knowledge retrieval and automated report-generation use cases.
Credit Suisse
Country risk pipeline and dashboards
Backend and frontend delivery on Palantir Foundry to support key metrics, insight communication and stakeholder decision-making.
Earlier UBS work
AI proofs of concept and automation
Solution design and experimentation across automation and AI use cases, from requirements gathering to delivery.
Research
Medical imaging and computer vision
Machine learning research with published work in lung tissue classification, segmentation and multimodal retrieval.
Leadership
Adoption, communication and delivery enablement
Crew-wide forums, roadmap representation, Confluence knowledge sharing and cross-team Agile coaching in delivery settings.
Credentials
Education and research
- MEng in Electrical and Electronic Engineering, Imperial College London
- Doctoral research in machine learning and medical imaging, ETH Zurich
- Publication record across journals, conferences and workshops
Executive learning and development
- AI Strategy and Leadership Program
- Leadership and Communication
- Managing People and Teams
- Active contributor in the GenAI Global @ MIT community
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