At least 3 years of experience working with data (analysis, data science, or data engineering)
Experience in data mining, including hypothesis formulation and testing, target definition, and performance evaluation (coverage, lift, robustness) just only on side projects, testings previous position, pandas, puspark , polars
Ability to deliver high-quality results, even for routine and repetitive tasks
Hands-on experience with PySpark for ETL and data transformations
Practical knowledge of Pandas or Polars (at least one required)
Experience with Git and version control tools (Bitbucket or GitHub)
Ability to follow best practices for production Python code (Jupyter for exploration, clean .py files for production)
Strong communication skills, with the ability to collaborate with both analysts and business units
Comfortable working in an iterative environment, incorporating feedback
Proactive mindset, able to propose and implement new data-driven hypotheses
Good command of English (written and spoken)

Data Analyst

Key skills