Senior Data Scientist (m/f/d)

Background

Join Next Level Coffee, the trailblazers behind nunc., our cutting-edge IoT coffee ecosystem. We're on a mission torevolutionize home coffee experiences with our premium products—coffee machine, grinder, app, and more. Launching in 2025, nunc. combines innovation and convenience for coffee lovers everywhere. With strong financial backing and a dynamic team, we're poised for rapid growth. Ready to transform the way the world enjoys coffee?Join us!

So what is the role?

You support our team by leading data resear ch and algorithm development that directly improves coffee quality and personalization. You work at the intersection ofdata, sensory science, and engineering to turn raw machine signals into meaningful insights and repeatable excellence in every cup.

• You develop and refine data models that improve consistency and flavor outcomes in espresso brewing.
• You are responsible for analyzing machine and sensor data to identify key variables influencing coffee quality.
• You take on the design and validation of hybrid modeling approaches that combine statistical methods , physics-based reasoning , and data-driven techniques .
• You contribute to the creation of predictive models that help detect performance drifts and optimize brewing parameters.
• You collaborate with coffee domain experts and engineers to translate your models into actionable insights for product and process improvement.

This is the next level you achieve after 6 months:

• You have delivered validated algorithmic approaches that measurably improve beverage consistency and reproducibility.
• You have established a systematic process for exploratory data analysis, model validation, and experiment evaluation, building on the existing data infrastructure.
• You have identified the most critical machine and environmental factors affecting coffee quality and quantified their impact.
• You are recognized as a core contributor who bridges scientific reasoning and practical application , working closely with data engineering, platform, and coffee teams.

What you need for this role:

• A Master’s or PhD in Physics , Applied Mathematics , Statistics , or a related quantitative discipline with a strong theoretical foundation.
• 7+ years of experience applying data science to complex, real-world problems, ideally in IoT, manufacturing, process optimization, or other sensor-driven systems.
• Proven mastery of statistical inference, causal modeling, Bayesian reasoning, and uncertainty quantification.
• Expertise in advanced modeling techniques, such as Bayesian optimization, Gaussian processes, probabilistic programming, and hierarchical modeling.
• Deep understanding of experimental design, simulation-based modeling, and system identification for complex physical or hybrid systems.
• Advanced proficiency in Python , with hands-on experience using scientific and probabilistic frameworks such as NumPy, SciPy, PyMC, GPyTorch, or TensorFlow Probability.
• Experience guiding the full data science lifecycle : from framing questions and defining success metrics to model evaluation and scientific communication.
• Ability to synthesize domain knowledge , collaborate with specialists , and translate scientific insights into scalable, data-informed product improvements.

What we deliver on:

• We want to do great stuff with a great team – this only works with a#nofilter and#nobullshit attitude .
• Huge opportunity to join early stage andbuild a company – you work on our common vision, product and values!
• You are best in class – and are enabled to makebest in class decisions.
• We loveworking visually and with the end result in mind, then get there by building fast and learning fast.
• We love humans, we love coffee and working with the coffee community,from farm to cup.
• Hybrid working - you work remotely, but once a month we meet for 2-4 days in Konstanz, the Alps, or Mallorca.
• Yourhome office setup tailored to your workday needs.
• Fitness programs ,childcare subsidies , ahome coffee supply , and many more benefits await you.

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