Senior Data Scientist - Demand Forecasting & Production ML

Fetcherr; Kraków; On-site; PLN 180,000 - 240,000; Full time

Job summary

Fetcherr in Kraków is seeking a seasoned Data Scientist to advance econometric and machine learning models for demand forecasting that translate into measurable profit growth. You will leverage Python and the ML stack to build accurate forecasts and robust pipelines.

You will collaborate with product, data engineering, MLOPS and Platform to deploy models in production, communicate findings to executives, and push for improvements in accuracy and scalability, applying state-of-the-art techniques

Qualifications

• 5+ years of hands-on data science with proven business impact.
• Proficiency in Python and ML stack (PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn).
• Expertise in time-series forecasting, ideally Deep Learning based, in demand prediction.
• Feature engineering and explainability, with model validation.
• Master’s or PhD in CS/ML/Statistics or related field.
• Strong ML production knowledge (versioning, testing, reproducibility, deployment).
• Excellent communication and collaboration skills.

Responsibilities

• Develop and implement state-of-the-art econometric and ML models for demand forecasting.
• Experiment to improve accuracy, robustness, and scalability.
• Collaborate with product, data engineering, MLOPS and Platform to deploy ML systems in production.
• Communicate complex technical findings clearly to non-technical stakeholders.

Skills

Python

Time-series forecasting

Deep Learning

ML Ops

Communication

PyTorch

Pandas

Education

Master’s or PhD in CS/ML/Statistics

Tools

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Job description

Fetcherr in Kraków is seeking a seasoned Data Scientist to advance econometric and machine learning models for demand forecasting that translate into measurable profit growth. You will leverage Python and the ML stack to build accurate forecasts and robust pipelines.

You will collaborate with product, data engineering, MLOPS and Platform to deploy models in production, communicate findings to executives, and push for improvements in accuracy and scalability, applying state-of-the-art techniques