About the role

Data Scientist analyzing complex IoT datasets to inform product and operational decisions at Jungheinrich. Collaborating with teams to develop insights and prototypes in a flexible, hybrid working environment.

Responsibilities

Dive into large, complex IoT datasets to uncover trends, anomalies and opportunities that inform product- and operational decisions
Use statistical and machine learning techniques to surface meaningful patterns, relationships or indicators that shape better product experiences and create meaningful impact for customers
Contribute to Product Discovery & Development Work hand-in-hand with product teams during the discovery & development phase: framing problems, identifying opportunities, and evaluating what’s worth building
Develop lean, targeted PoCs to validate ideas quickly, refine what works and pave a clear path towards stable, production-ready customer solutions
Validate & Collaborate in the Real World Partner with sales, customer-facing teams, and product owners to test assumptions early, validate the value of insights, and co-create solutions that customers will use
Ability to take ownership of the prototyping process - from defining objectives and setting clear goals to delivering a functional, shippable prototype - while embracing feedback and iterating for continuous improvement

A masters’ degree or PhD in a related field
3+ years of hands-on experience in data science
Foundation in statistics and machine learning - both theory and practice
Familiarity with or willingness to learn probabilistic modelling techniques (e.g. Bayesian inference, probabilistic programming or uncertainty quantification) or interest in learning them as a key skill
Hands-on experience with Python (preferred), and common data science libraries (e.g., Pandas, NumPy, Scikit-learn)
Familiarity with SQL and NoSQL databases (e.g. PostgreSQL, MongoDB)
Solid grasp of data wrangling, exploratory data analysis and experiment design
Curiosity-driven mindset with strong problem-solving skills and a willingness to experiment
Clear and concise communication skills, especially when explaining data findings to non-technical teammates
Eagerness to learn, grow and be mentored - especially in shaping data science that’s actionable, practical, and valuable
Excellent knowledge of English
Nice to have: Experience with IoT data or time-series data, especially in manufacturing, logistics, or intralogistics
Exposure to cloud platforms (AWS, GCP, Azure) or machine learning frameworks (TensorFlow, PyTorch), big data processing tools (Spark or Databricks)

Attractive salary depending on your qualifications and experience
Flexible working hours and the opportunity of working from home
A pleasant working atmosphere with a "first-name" culture in a company where employees come first
Challenging, independent work in an innovative, creative environment
Language courses
Health and recreation benefits
Family incentives
Healthy snack and coffee for free in a brand-new office in Zagreb
Lots of internal events - so that we don't miss out on having fun together
Professional and personal training opportunities for your further development