Data Scientist – Warsaw
Core
Build regression models and statistical pipelines for spectroscopic data to assess food and agricultural product quality using a handheld spectrophotometry kit.
Role type
Data Scientist (Machine Learning & Statistics)
Builds
Production ML models for in-situ nutrient analysis and quality assessment
Domain
Public health, food security, agronomy, chemometrics
Deliverable
production ML models | dashboards & analysis
Required skills
regression modeling, experimental design, feature engineering, chemometrics, Python, Git, statistical hypothesis testing, time series analysis, neural networks
Preferred skills
spectroscopy (Vis/NIR/MIR), calibration transfer, multi-instrument dataset handling, food chemistry, sustainable development goals
Technologies
Python, Git, CI/CD, PLSR, SVR, Extra Trees, RCTs
Responsibilities
Build and improve regression models for spectroscopic data; Plan sampling strategies and real-world experimental design; Design robust training/evaluation pipelines; Apply chemometrics best practices to spectral data; Diagnose model failures and data issues; Construct dashboards/reports to visualize data analytics; Collaborate with engineering/product to deploy models; Assist in communication with scientific institutes and researchers; Collaborate on research papers and impact reports
Seniority
Mid-level, hands-on IC