Data Scientist working at HP analyzing complex data sets using statistical techniques. Developing data - driven models and insights to improve organizational performance while mentoring project teams.
About the role
- Data Scientist leading data research and algorithm development for Next Level Coffee's innovative coffee products. Collaborating to improve coffee quality and personalization through data-driven insights.
Responsibilities
- You support our team by leading data research and algorithm development that directly improves coffee quality and personalization
- You work at the intersection of data, 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
- 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
Requirements
- 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
Benefits
- Hybrid working - you work remotely, but once a month we meet for 2-4 days in Konstanz, the Alps, or Mallorca
- Your home office setup tailored to your workday needs
- Fitness programs
- Childcare subsidies
- A home coffee supply
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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