Data Scientist

Jobtailor; Kraków; On-site; PLN 240,000 - 360,000; Full time

Job summary

Jobtailor in Kraków seeks a Senior Data Scientist to develop and implement econometric and machine learning models for demand forecasting. You will collaborate with product, data engineering, MLOPS, and Platform teams to deploy ML systems into production.

Applicants have 5+ years in data science, strong Python and ML stack skills (PyTorch/TensorFlow, Pandas, NumPy, scikit-learn), and a Master’s or PhD. Experience with cloud (GCP) and ML production workflows is highly valued.

Qualifications

• 5+ years of hands-on data science and ML with proven business impact.
• Proficiency in Python and ML stack (PyTorch/TensorFlow, Pandas, NumPy, Scikit-learn).
• Expertise in time-series forecasting, ideally deep-learning based.
• Experience with feature engineering and explainability.
• Master’s or PhD in CS/ML/Statistics or related field.
• Strong ML production workflow knowledge: versioning, testing, reproducibility, deployment.
• Excellent communication and collaboration skills.
• Publications in top ML venues are a plus.
• Experience applying ML in finance, trading, revenue management is a plus.
• Familiarity with GCP (Vertex AI, Pub/Sub, Cloud Run).
• Strong data visualization and exploratory data analysis skills.
• Familiarity with Docker, CI/CD, cloud-native architectures.
• Participation in Kaggle or similar challenges is a plus.

Responsibilities

• Develop and implement econometric and ML models for demand forecasting.
• Conduct research to improve accuracy, robustness, and scalability.
• Collaborate with product, data engineering, MLOPS, and Platform teams to deploy ML systems in production.
• Communicate complex findings clearly to non-technical stakeholders.
• Advance Fetcherr’s ML capabilities and deliver measurable business impact.

Skills

Python proficiency

Time-series forecasting

ML production workflows

Communication skills

Publications nice to have

Education

Master’s or PhD in CS/ML/Statistics

Tools

Python

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

GCP

Vertex AI

Docker

CI/CD

Job description

• Develop and implement state-of-the-art econometric and machine learning models for demand forecasting
• Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability
• Collaborate with product, data engineering, MLOPS, and Platform teams to deploy ML systems in production
• Communicate complex technical findings clearly to non-technical stakeholders, including product leaders and executives
• Advance Fetcherr’s machine learning capabilities and deliver measurable business impact

Requirements

• 5+ years of hands-on experience in data science and machine learning with a proven record of leveraging modeling into business outcomes
• Proficiency in Python and its ML/data stack, including PyTorch or TensorFlow, Pandas, NumPy, and Scikit-learn
• Expertise in time-series forecasting, ideally deep-learning based, preferably in demand prediction or related areas
• Experience with feature engineering, feature importance testing, and explainability
• Master’s or PhD in Computer Science, Machine Learning, Statistics, Engineering, or a relevant field
• Solid understanding of ML production workflows, including versioning, testing, reproducibility, and deployment
• Excellent communication and collaboration skills
• Publications in top-tier, peer-reviewed ML/AI venues are nice to have
• Experience applying ML in finance, trading, revenue management, or related domains is nice to have
• Familiarity with cloud-based solutions on GCP, such as Vertex AI, PubSub, and Cloud Run Functions, is nice to have
• Strong data visualization and exploratory data analysis skills are nice to have
• Familiarity with code optimization, containerization such as Docker, CI/CD, or cloud-native architectures is nice to have
• Participation in competitive programming or data science challenges such as Kaggle is nice to have

Core Competencies

Demonstrates expertise in developing and implementing econometric and machine learning models for demand forecasting, with a strong focus on Python and its ML/data stack. Proven ability to communicate complex technical findings to non-technical stakeholders and deliver measurable business impact.

Highest-signal resume keywords

• Machine Learning Expertise
• Python Proficiency
• Time-Series Forecasting
• ML Production Workflows
• Data Science Experience

Hard Skills

• Machine Learning
• Econometric Modeling
• Time-Series Forecasting
• Feature Engineering
• Data Analysis
• Model Deployment
• Statistical Analysis
• Deep Learning
• Data Visualization
• Exploratory Data Analysis

Soft Skills

• Communication Skills
• Collaboration Skills

Certifications & Qualifications

• Master’s Degree
• PhD

Industry Keywords

• Demand Forecasting
• Finance
• Trading
• Revenue Management
• Machine Learning in Business

Tools & Technologies

• Python
• PyTorch
• TensorFlow
• Pandas
• NumPy
• Scikit-learn
• GCP
• Vertex AI
• Docker
• CI/CD