Data Scientist

Das ist der Job

Responsibilities Act as the central data expert and Business Data Steward for the German Mortgages business.

Darum lohnt es sich

Serve as the key interface between Mortgages and the Business Intelligence team, translating business requirements into data, reporting and dashboard solutions.

Experience working with multiple source systems, complex data flows and cross‑functional teams across business, technology and BI functions. #J-18808-Ljbffr Analyse customer, product, portfolio, channel and risk data to provide insights, identify trends, detect anomalies and support business decision-making.

Deliver portfolio analytics, forecasting, scenario analysis and ad hoc management reports to support strategic initiatives, product enhancements and business growth. Design, develop and maintain Power BI dashboards, reports and monitoring tools, while driving automation and efficiency in reporting processes.

Own and maintain data definitions, business rules, Critical Data Elements (CDEs) and data standards across the Mortgages function. Ensure consistent use of data, high data quality and adherence to agreed business logic and controlled data sources.

Define and monitor data quality controls, investigate data issues and coordinate corrective actions with data, technology and business stakeholders. Support projects, change initiatives and continuous improvement activities as the primary contact for data-related topics.

Promote data literacy and a data-driven culture across the Mortgages department. Qualifications Bachelor’s degree in Business, Information Technology or a related discipline.

Several years of experience in Data Science, Data Analytics, Business Intelligence, Portfolio Analytics or Data Stewardship, ideally within banking, mortgages or financial services. Strong analytic, problem‑solving and stakeholder management skills, with the ability to translate business needs into actionable insights and recommendations.

Advanced experience with Power BI, SQL, Databricks (Python/PySpark) and handling large and complex datasets. Good understanding of Azure‑based data environments, including data warehousing, ELT processes, Databricks, Unity Catalog, cluster configuration and Azure Data Factory (ADF).

Sound knowledge of data governance, data quality management, data lineage, Critical Data Elements (CDEs) and data ownership principles.