3 beste Stellen als data scientist in leipzig – aktuell auf Personalsuche

Researcher / Data Scientist (f/m/x) for AI-enabled Environmental Data Harmonisation and Quality Control
Helmholtz-Zentrum für Umweltforschung UFZ —Leipzig
- Vollzeit
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- Datenanalyse
- Master
- Flexible Arbeitszeiten
4 Tage
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Researcher / Data Scientist (f/m/x) for AI-enabled Environmental Data Harmonisation and Quality Control

Helmholtz-Zentrum für Umweltforschung UFZ -
Leipzig

Jetzt bewerben

Details zur Stelle

Vollzeit
vor 4 Tagen

Leistungen

Jobticket
Flexible Arbeitszeiten

Qualifikationen

Doktorat
R
Datenanalyse
Master
Machine Learning
Datenpflege
APIs
Künstliche Intelligenz
Python

Vollständige Stellenbeschreibung

Place of work

Leipzig, remote working partially possible

Working time

100% (39h/week)

The job position is available for full-time or part-time employment.

Contract limitations

limited contract

Salary

Remuneration according to the TVöD public-sector up to pay grade 13 including attractive public-sector social security benefits.

Contact

Your contact for any questions you may have about the job:
Ulf Mallast ([email protected])
Martin Abbrent ([email protected])

Your application

To ensure a fair selection process, please submit your application (cover letter, CV, and relevant supporting documents) via our online portal without a photo, age information, or details about your marital status.

Diversity and Inclusion

The UFZ values diversity and is actively committed to ensuring equal opportunities for all employees, regardless of their origin, religion, beliefs, disability, age or sexual identity.
We welcome people who represent diverse backgrounds, identities and perspectives. We therefore particularly encourage people who are affected by structural discrimination to apply to us.

The UFZ

The Helmholtz Centre for Environmental Research (UFZ) is a world-leading institution in environmental research and a member of the Helmholtz Association, Germany’s largest scientific organisation. With approximately 1,200 employees across Leipzig, Halle, and Magdeburg, we have been conducting research since 1991 using a transdisciplinary approach to address the most pressing challenges of our time: biodiversity loss, climate change, and environmental pollution. Our goal is to translate excellent research into practical solutions for policymakers, business, and society, and to serve as a reliable partner in supporting transformation processes toward a sustainable and just future for current and future generations. We foster a culture of collaboration, openness, and diversity within a work environment that actively promotes creativity and personal development.

The job

UFZ is the lead institution of the eLTER ESFRI process, aiming at the establishment of the Integrated European Long-Term Ecosystem, critical zone and socio-ecological Research Infrastructure (eLTER RI, eLTER-RI.eu) in the context of the high level strategic platform for the development of priority European RIs (European Strategy Forum on Research Infrastructures, ESFRI, https://www.esfri.eu/). The UFZ campus in Leipzig hosts the eLTER Head Office, which manages the eLTER ERIC legal entity and coordinates related eLTER projects and activities in close collaboration with the University of Helsinki.

165 scientific institutions in 28 countries and 26 national LTER networks have been collaborating in this process and creating the pan-European distributed physical network of > 250 highly instrumented ecosystem and socio-ecological research sites.Reliable environmental AI depends on trustworthy, harmonised and continuously quality-controlled data. At UFZ and eLTER, we develop scalable workflows that transform heterogeneous observations from distributed research sites and data platforms into interoperable, traceable and AI-ready data products.We are looking for a Researcher or Data Scientist to develop and operationalise AI-enabled workflows for the harmonisation, curation and quality assurance of environmental data and other applications. The position connects distributed environmental research infrastructures, continuously generated observation data and emerging AI models, translating methodological developments into reproducible and scalable workflows for scientific and operational use.

Your tasks

We are seeking a highly motivated Researcher or Data Scientist (f/m/x) with experience in scientific data management and applied AI. The successful candidate will undertake the following tasks:

Design and operate scalable workflows for the ingestion, integration, deduplication and harmonisation of heterogeneous environmental observation and research data, including traceable provenance, metadata enrichment and semantic annotation
Develop and evaluate hybrid QA/QC methods combining established rule-based and statistical procedures with machine-learning approaches for anomaly detection, gap filling, sensor-drift detection and uncertainty-aware quality assessment
Benchmark and evaluate AI-enabled QA/QC methods against established approaches using heterogeneous environmental and sensor-based time-series datasets, with particular emphasis on robustness, explainability and transferability across data sources and domains
Transform research prototypes into tested, reproducible and maintainable data pipelines and services suitable for continuous data ingestion and operational use, including contributions to tools such as SaQC
Prepare curated training and evaluation datasets and contribute to the assessment and adaptation of environmental and cross-domain foundation models
Collaborate with environmental researchers, data managers, software engineers and international project partners, and contribute to technical documentation, reusable guidelines, training materials and scientific publications

We offer

The freedom to master even the most demanding challenges between basic research and practical application
The chance to work in interdisciplinary, international teams and benefit from a variety of perspectives
Firstclass integration into national and international research networks to work together on global challenges
Excellent research infrastructure and research data management to optimally support your work
Flexible working hours and a wide range of options for balancing work and care responsibilities through our family office
Competent support and advice for international colleagues arriving at the UFZ from the 'International Office'
Special annual payment, capital-forming benefits and subsidised Germany Job Ticket
A workplace in a vibrant region with a high life quality and social and cultural diversity

Your profile

A university degree, preferably at Master’s or PhD level, in Data Sciences, Computer Sciences, Environmental Informatics, Geoinformatics, Environmental Sciences, or a related field
Strong programming skills in Python or R and experience with established data-science and machine-learning libraries
Experience in one or more of the following areas: time-series analysis, anomaly detection, data imputation, uncertainty quantification, machine learning or AI-enabled data analysis
Experience with environmental, ecological, geoscientific, sensor-based or similarly heterogeneous scientific datasets
Experience in developing reproducible data-processing workflows, including version control, testing and collaborative software development
Familiarity with FAIR data principles, metadata standards, semantic technologies, APIs or interoperable research data infrastructures is an advantage
Highly welcome: Experiences with and/or connections to EOSC
Ability to work independently and collaboratively in an interdisciplinary and international environment
Very good communication skills in English and German

Application deadline: 02.08.2026

More information about jobs at the UFZ:
www.ufz.de/career

LinkedIn @UFZ

Family Support

International Office

Accessibility

Diversity, Equity & Inclusion

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data scientist Jobs in leipzig

Researcher / Data Scientist (f/m/x) for AI-enabled Environmental Data Harmonisation and Quality Control

Expert Data Analytics (m/f/d)

Senior AI Engineer (m/f/d)

Discover related jobs

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