Thomas Glaus

As the Chief Data Officer (CDO), I am responsible for the data strategy and shape the data and analytics landscape onprem and in the cloud. My focus is on data architecture, data governance, data culture, data management, data monetization, and AI. I not only develop the strategy but also implement it operationally across all components – with a clear focus on scalability, efficiency, and regulatory compliance. My goal: to make the bank future-proof and transform it into a leading data-driven organization.

At Cembra, I led an interdisciplinary team and was responsible for the bank's Data & AI strategy. My focus was on transforming data platforms to the cloud, implementing innovative data governance and analytics approaches, and integrating modern machine learning solutions. Through close collaboration with business and IT stakeholders, I was able to realize sustainable added value and efficiency improvements.

In my role as Head of Data Management at Denner, I was responsible for reorienting the data strategy and building a powerful BI and analytics infrastructure. I developed an innovative DWH architecture for the "Golden Record" and optimized the analytical basis for data-driven business decisions. My data strategy approach optimized processes and significantly advanced digitalization within the company.

At Swiss Life, I led data-driven projects with a focus on BI, data science, and cloud strategies. I built a powerful data platform, developed machine learning models, and established a sustainable data analytics roadmap. Through my work, the company was able to optimize data-driven decision-making processes and sustainably increase the value created from data.

As Head of Client Analytics at Zürcher Kantonalbank, I was responsible for establishing and further developing analytical processes for customer and market segmentation. I developed innovative ML and AI models to optimize sales and consulting processes, built data warehouses, and implemented hybrid cloud architectures. My work led to significant revenue increases through targeted, data-driven sales and marketing measures.

At UBS, I worked as a data scientist and pricing analyst, developing machine learning models for marketing and sales management. I analyzed large amounts of data to optimize pricing strategies and developed predictive models for customer behavior. My data-driven approaches led to improved sales strategies and more efficient segmentation of the client portfolio.

CAS Information Engineering, CAS Data Analysis, CAS Data Science Applications, CAS Data Product Design, Master Thesis in Data Science

Corporate Finance, Wirtschaftsrecht und Volkswirtschaftslehre, Strategisches Management, Marketingmanagement, Operations- und Projektmanagement, Human Capital Management und Leadership, International Management

Wahrscheinlichkeitstheorie, statistische Datenanalyse, Finanzmathe & stochastische Modellierung der Finanzmärkte, Ingenieurphysik, Analysis, lineare Algebra, Differentialgleichungssysteme, Elektrotechnik, Ökonometrie, Survey Design, Relationale DBs, Matlab, R, S-Plus, SQL, Java