Data Scientist

Job Description

About Us

At Omegga, we’re on a mission to reinvent how AI and science can drive positive change for animals, people and the planet. Outdated practices still impact billions of lives, and we’re here to change that.

Five years ago, we began in the poultry industry with a bold idea: use breakthrough AI-powered spectroscopy to revolutionise the industry by identifying chick gender before hatching to spare billions of male chicks.

With the support of our customers, investors and the European Commission, we are ready for the next chapter in poultry while exploring new applications. Join us and help shape a future where innovation drives meaningful change.

www.omegga.de

What We Are Looking For

We are looking for a Data Scientist to own the operational data lifecycle between our hardware systems and model improvement, ensuring that machine-generated data is reliable, traceable, and continuously driving measurable system and algorithm performance improvements.

This role sits at the intersection of hardware, operations, and AI. You will work with real-world, high-frequency machine data, build robust validation and monitoring workflows, and create structured feedback loops that enable hypothesis-driven analysis, dataset curation, and continuous improvement of our models and systems.

Your mission

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• Ensure data quality, validation, and traceability: monitor incoming data streams from field systems, validate completeness and consistency, detect anomalies, drift, or missing metadata, and develop automated validation workflows and monitoring dashboards.
• Drive operational analysis and performance insights: analyze classification results and system behavior across devices, sites, and batches; investigate deviations and unexpected outcomes; identify confounding factors; and produce structured performance and incident analysis reports.
• Own dataset curation and data operations: perform large-scale data cleaning and restructuring, curate high-quality training datasets, maintain data catalogs, and ensure datasets are reliable, structured, and usable for model development and evaluation.
• Run hypothesis-driven analysis and experimental data initiatives: design and execute exploratory analyses and controlled experiments in collaboration with hardware and ML teams, uncover new patterns and system behaviors, and propose targeted data collection strategies to close performance gaps.
• Build structured feedback loops across teams: translate model outputs into actionable insights, collect and integrate real-world operational feedback, and act as the interface between hardware operations, data workflows, and ML engineering to continuously improve system performance.
  
  

Your profile

• Strong analytics and data science foundation: several years of experience in data analytics, data science, or applied statistics, ideally working with sensor, time-series, or machine-generated data in real-world environments.
• Hands-on with data tooling and data operations: strong SQL and Python skills (e.g., pandas, numpy), with experience cleaning, restructuring, validating, and analyzing large and complex datasets.

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• Experience with data quality, monitoring, and validation: ability to design validation checks, detect anomalies or drift, and ensure traceability and integrity across data pipelines and datasets.
• Applied statistical reasoning and experimental thinking: confidence in hypothesis-driven analysis, experimental design, statistical interpretation, and identifying root causes in noisy, real-world systems.
• Strong communication and cross-functional ownership: ability to clearly communicate findings, write structured analysis reports, and collaborate effectively with hardware, operations, and ML engineering teams.
  
  

Nice to have

• Experience with anomaly detection, condition monitoring, or performance analysis in industrial, robotics, spectroscopy, or IoT environments
• Experience curating training datasets and supporting ML evaluation workflows, including labeling strategies, dataset versioning, and performance tracking
• Familiarity with designing and analyzing controlled experiments in hardware-software systems
• Experience building dashboards or automated monitoring tools to track system and data health

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• Comfortable using AI-assisted tools to accelerate analysis and data workflows while maintaining correctness and reproducibility
  
  

Why us?

• Mission-driven team: At Omegga, you’re not just an employee, you’re part of a purpose-led journey, working on a solution with a tangible global impact.
• Relocation Support: Fully furnished, affordable apartment within 3 minutes walking distance of the office (up to 6 months).
• VSOPs: Above average company participation package
• Modern Work Environment: A beautiful office in Munich’s Werksviertel, with up to 50% remote work.
• Perks: Monthly voucher where you can choose between 100+ partners (e.g., Urban Sports, D-Ticket, REWE, Rossmann, IKEA).
• Competitive Salary: Market-aligned compensation recognising your skills and contributions.
• Vacation: 28 paid vacation days per year.