Data Scientist (f/m/d)
At a glance
Mid-level Data Science role at Deutsche Börse. Luxembourg, LU.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Shape curated datasets, semantic models and analytics products from initial requirements through delivery
- Build and maintain data flows on Databricks with SQL, Python and PySpark
- Create Power BI dashboards, reports and self-service analytics for users
- Test machine learning and AI methods on business and operational needs, then help deploy solutions
- Build data quality, governance, lineage and performance into the data lifecycle
What you bring
- A relevant master’s degree in a quantitative discipline such as data science, engineering or mathematics
- At least two years developing data science, analytics or data engineering solutions
- Strong SQL and Python skills, with practical PySpark use and experience on Databricks or a similar cloud platform
- A track record building semantic models, data products and Power BI dashboards, plus applying AI or machine learning
- Knowledge of investment funds, fund administration or financial services data, and fluent English
Who this fits
This role suits a mid-level practitioner who can work across data science, engineering and analytics, and explain findings to technical and non-technical audiences. You’ll collaborate with business, IT, product and governance teams and take part in Agile planning and reviews.
From the employer
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.
- Knowledge of the investment funds industry, fund administration or financial services data environments.
- 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.
- Fluent in English; additional European languages would be considered an advantage.
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