Job
- Level
- Experienced
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Osnabrück
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop machine learning solutions for evaluating water pipeline integrity by analyzing and validating sensor and image data, and implementing cloud-based software.
Job Technologies
Your role in the team
- Rosenxt is seeking a skilled Data Scientist to join our team.
- This role is ideally suited to someone who is passionate about solving complex problems with data, and delivering measurable value through classical and machine learning methods.
- In this role, you'll work on cutting-edge technology that makes a real-world impact - initially developing data science and machine learning solutions within the Water Line Integrity Solutions group.
- This group focuses on developing advanced technologies for the inspection and assurance of water pipeline integrity.
- Our state-of-the-art inspection devices autonomously travel through water pipelines, gathering extensive data, including video and ultrasound data.
- To evaluate this data, we develop cloud-based software solutions that utilize classic signal processing algorithms, computer vision, and machine learning.
- Translate business and product goals into well-defined data science and machine learning problems, identifying where data-driven approaches can generate the most value.
- Conduct rigorous data analysis and experimentation, identifying patterns, quantifying uncertainty, and adapting strategies based on findings.
- Design, develop, and validate machine learning models and analytical workflows, advancing solutions from research to production.
- Define success metrics and key performance indicators in collaboration with stakeholders, ensuring solutions deliver measurable business impact.
- Produce clear documentation, visualisations, reports, and dashboards for both technical and non-technical audiences.
- Validate data quality, recommend improvements to data collection processes, and identify risks including model bias, drift, and fairness concerns.
- Stay current with advances in statistical and machine learning methods, tools, and industry best practices, assessing their applicability to our goals.
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Our expectations of you
Qualifications
- Solid understanding of supervised and unsupervised learning algorithms, statistics, and linear algebra.
- Practical skills in statistical analysis, data visualisation, and feature engineering.
- Clear and comprehensive documentation of code, methods, and experiments.
- Ability to implement algorithms from academic papers.
Experience
- Proven experience designing experiments, building models, and delivering data science solutions in production.
- Hands-on experience applying ML and statistical methods to complex real-world data (e.g., sensor data, time series, signal recordings).
- Strong proficiency with Python and core data science libraries (e.g., PyTorch, scikit-learn, pandas, numpy), or strong experience in other languages and a willingness to learn Python.
- Experience with Git, environment management (e.g., Docker, Poetry, uv), and at least one major cloud platform (AWS, Azure, or GCP).
- Experience processing ultrasound data & video data.
- Experience with PyTorch, PyTorch Lightning, OpenCV, CVAT, Docker, ROS.
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Benefits
Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
Rosenxt Group
Rosenxt Group specializes in developing innovative technologies in industrial diagnostics and plant safety. With a strong focus on research and development, the company provides tailored solutions for complex challenges.
Description
- Company Type
- Established Company
- Working Model
- Full Remote, Hybrid, Onsite
- Industry
- Electronics, Automatization
Data Scientist
- Location
- Osnabrück
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
