Perform exploratory data analysis (EDA), preprocessing, and data validation;
Define, calculate, and monitor KPIs and statistical/performance metrics (PSI, KS, Gini, AUC, Precision/Recall);
Apply statistical techniques and supervised and unsupervised methods;
Process, consolidate, and validate datasets for analytical use;
Develop analyses and models using Python (Pandas, NumPy, Scikit-learn, XGBoost, SHAP);
Work with Big Data using PySpark and EMR;
Work with AWS services (S3, Athena, Glue, DynamoDB, Lambda);
Monitor pipelines, versioning, and stability of data stores;
Continuously interact with data engineering and business stakeholders;

Experience in exploratory data analysis and data preparation;
Strong knowledge of Python for analysis and modeling (Pandas, NumPy, Scikit-learn, XGBoost, SHAP);
Experience with Big Data using PySpark and EMR;
Experience with AWS (S3, Athena, Glue, DynamoDB, Lambda);
Knowledge of statistical and performance metrics (PSI, KS, Gini, AUC, Precision/Recall);
Experience in monitoring and data quality control;
Ability to communicate insights and collaborate with technical and business teams;

Data Analyst

Key skills