Senior Data Scientist (Personalisation)

TL;DR

Senior Data Scientist (Personalisation): Developing and implementing machine learning models and data-driven solutions to optimize marketing strategies and enhance user experience within the hirify.global ecosystem. Focus on building end-to-end data products, from business problem analysis to model deployment and monitoring, while collaborating with cross-functional teams.

Location: Must be based in Kraków, Poland

Company

hirify.global is a leading European e-commerce enablement platform providing automated parcel delivery services through an extensive network of lockers and pick-up points.

What you will do

• Partner with product and business teams to translate needs into actionable data science solutions.
• Develop and implement ML models, GenAI products, and data analytics to shape targeting and product strategies.
• Collaborate with cross-functional teams to ensure seamless integration of data-driven initiatives.
• Communicate insights and recommendations to management and non-technical stakeholders.
• Maintain and monitor deployed solutions to ensure ongoing performance and business impact.
• Stay updated on cutting-edge methods and trends in Data Science and AI.

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, or Econometrics.
• At least 3 years of commercial experience as a Data Scientist.
• Proficiency in Polish and English.
• Excellent knowledge of ML solutions including clustering, recommender systems, regression, and classification.
• Strong proficiency in Python and data analysis libraries like Pandas, Numpy, and Scikit-learn.
• Experience with PySpark, relational databases, and cloud platforms such as Databricks, Azure, GCP, or AWS.

Nice to have

• Experience with CI/CD pipelines for data products.
• Knowledge of data pipeline frameworks like Kedro.
• Proficiency with CLI tools like bash/zsh.

Culture & Benefits

• Opportunity to influence strategic decisions across multiple international markets.
• Work in a technology-forward environment with the latest data analytics methodologies.
• Engagement with cross-functional teams in a culture of continuous learning.
• B2B contract employment model.