Senior Data Science Research Engineer (m/f/d) – Instrument Analytics

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue of approximately $40 billion. Our Mission is to enable our customers to make the world healthier, cleaner and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, increasing productivity in their laboratories, improving patient health through diagnostics or the development and manufacture of life-changing therapies, we are here to support them. Our global team of more than 100,000 colleagues delivers an unrivaled combination of innovative technologies, purchasing convenience and pharmaceutical services through our industry-leading brands, including Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon and PPD.

Location/Division Specific Information

We are a research, development, and production site in Bremen currently, with about 500 employees, whose “high-end” measurement and analysis instruments (mass spectrometers) are used in research and science worldwide. Our innovative products in the fields of Life Sciences MS and Inorganic MS, as well as Trace Elemental Analysis, are among the leading products globally in their respective markets. We are currently seeking a highly skilled and experienced Senior Scientist to join our dynamic Research & Development team in Bremen. 

The Senior Data Science Research Engineer focuses on extracting scientific and product insights from large-scale instrument data to directly improve performance, calibration, and reliability of Thermo Fisher mass/optical spectrometry platforms. This role sits at the intersection of applied research, data science, and deep instrument knowledge, with a strong emphasis on focused, results-driven analysis rather than day-to-day feature development. This is an on-site position based in Bremen and requires regular hands-on access to spectrometers (including prototypes) and close collaboration with Production/Operations and Support during iterative validation, troubleshooting, and rollout preparation.

A day in the Life:

• Lead data-driven research initiatives using historical and live instrument data to improve calibration, stability, and performance.
• Apply classical statistics and machine learning / deep learning techniques to uncover non-obvious behaviors in complex hardware systems.
• Translate research findings into actionable improvements, including algorithms, procedures, and patentable innovations.
• Design, maintain, and leverage large-scale data pipelines (e.g., procdata-server–like systems) for scientific analysis.
• Collaborate closely with instrument physicists, firmware, and software teams while remaining primarily research-focused.
• Prototype and validate models and analysis tools in Python and related ecosystems, with pathways to production where appropriate.
• Contribute to intellectual property generation and technical strategy through exploratory but impact-oriented research.
• Work directly with spectrometers to extract insight from hardware data and domain knowledge and validate it with R&D and production
• Reproduce hardware behaviours, verify hardware configurations, and run controlled experiments to validate algorithm changes.
• Partner with Production Engineering, Operations, and Support to align on data capture, acceptance metrics, and rollout criteria; ensure metadata and traceability across instrument software, microservices, and test systems. Keys to Success:

Core Skills & Expertise

• Data Science & Machine Learning: statistical modeling, ML, deep learning, data manipulation, exploratory analysis.
• Programming: Python, C/C++, Rust, Java; strong systems programming background.
• Data & Infrastructure: SQL, NoSQL, Linux, Bash, DevOps, data pipeline architecture.
• Software Engineering: software design, testing, code review, test automation.
• Embedded & Instrument Systems: experience working close to hardware and embedded environments.
• Security & Reliability (secondary strength): cybersecurity, vulnerability assessment, penetration testing, network security.
• Instrument & production interaction: comfortable working hands-on with spectrometers and line-side test systems; understands acquisition workflows, sensor/telemetry signals, and data provenance.

Research & Impact Focus

• Proven ability to deliver high-impact insights when given protected time for deep analysis.
• Experience using historical instrument data to drive unexpected discoveries and measurable improvements.
• Demonstrated success in