Data Scientist (f/m/d)
Luxembourg
What you’ll work on
Full postingDevelop and enhance curated datasets, semantic models and analytical data products from requirements gathering through to delivery.
Build and maintain data pipelines using modern platforms such as Databricks, leveraging SQL, Python and PySpark.
Design dashboards, reports and self-service analytics solutions using Power BI and related technologies.
From the employer’s posting
Your responsibilities: Develop and enhance curated datasets, semantic models and analytical data products from requirements gathering through to delivery. Build and maintain data pipelines using modern platforms such as Databricks, leveraging SQL, Python and PySpark.
Develop and enhance curated datasets, semantic models and analytical data products from requirements gathering through to delivery. Build and maintain data pipelines using modern platforms such as Databricks, leveraging SQL, Python and PySpark. Design dashboards, reports and self-service analytics solutions using Power BI and related technologies.
Build and maintain data pipelines using modern platforms such as Databricks, leveraging SQL, Python and PySpark. Design dashboards, reports and self-service analytics solutions using Power BI and related technologies. Apply machine learning and AI techniques to develop, test and validate business and operational use cases.
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Tools in this posting
- python
- sql
- databricks
- pyspark
Source — Tool mentions in context
- Develop and enhance curated datasets, semantic models and analytical data products from requirements gathering through to delivery. - Build and maintain data pipelines using modern platforms such as Databricks, leveraging SQL, Python and PySpark. - Design dashboards, reports and self-service analytics solutions using Power BI and related technologies.
- Minimum 2 years of professional experience in data science, analytical solution development, data engineering or related areas. - Strong proficiency in SQL and Python, with hands-on experience using PySpark for data processing and analytics. - Experience working with Databricks or a comparable modern cloud-based data platform.
- Strong proficiency in SQL and Python, with hands-on experience using PySpark for data processing and analytics. - Experience working with Databricks or a comparable modern cloud-based data platform. - Proven experience developing semantic models, data products and Power BI dashboards.
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- Pay
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- Location & working pattern
Luxembourg
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Posting history
- Status in our records
- Active
- First seen by us
- Sep 7, 2026
- Recorded sightings
- 4
- Last seen by us
- Sep 8, 2026
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Report an errorJob description
Your area of work:
As a Data Scientist within the Data Analytics & Governance unit, you will contribute to the development of innovative data products, advanced analytics solutions and AI-enabled capabilities supporting Clearstream Fund Services. Working closely with business, IT, data product and governance teams, you will help transform complex data into valuable insights and scalable solutions that enhance decision-making, operational efficiency and client value across the investment funds industry. The role combines data science, data engineering and analytics, providing opportunities to contribute throughout the entire data lifecycle, from data preparation and modelling to visualization and business adoption.
Your responsibilities:
- Develop and enhance curated datasets, semantic models and analytical data products from requirements gathering through to delivery.
- Build and maintain data pipelines using modern platforms such as Databricks, leveraging SQL, Python and PySpark.
- Design dashboards, reports and self-service analytics solutions using Power BI and related technologies.
- Apply machine learning and AI techniques to develop, test and validate business and operational use cases.
- Support the industrialization and deployment of data and AI solutions in collaboration with business and technology stakeholders.
- Ensure data quality, governance, metadata, lineage, scalability and performance requirements are embedded throughout the data lifecycle.
- Contribute to Agile delivery activities, including user stories, backlog refinement, stakeholder reviews and solution prioritization.
- Communicate analytical findings, recommendations and technical concepts effectively to both technical and non-technical audiences.
Your profile:
- Master's degree in Data Science, Computer Science, Engineering, Mathematics or a related quantitative field.
- Minimum 2 years of professional experience in data science, analytical solution development, data engineering or related areas.
- Strong proficiency in SQL and Python, with hands-on experience using PySpark for data processing and analytics.
- Experience working with Databricks or a comparable modern cloud-based data platform.
- Proven experience developing semantic models, data products and Power BI dashboards.
- Practical experience applying machine learning and AI techniques to business or operational use cases.
- Knowledge of the investment funds industry, fund administration or financial services data environments.
- Fluent in English; additional European languages would be considered an advantage.