Applied / Production Data Scientist with hands-on experience across the full machine-learning lifecycle, from large-scale data preparation and feature engineering to model development, validation, and deployment in cloud environments.
Strong background in Python, SQL, Spark, and Databricks, with experience delivering production-ready ML and GenAI solutions using reproducible, containerized, and monitored architectures.
I have worked across marketing analytics, customer intelligence, and financial data domains, building predictive models for segmentation, churn, CLV, forecasting, and decision optimization. My work includes NLP-based content analytics, external API data pipelines, BI dashboards, and statistical analysis supporting real business decisions.
I collaborate closely with engineers, product teams, and business stakeholders, translating complex problems into scalable analytical solutions. My background combines data science, statistics, big-data engineering, and business leadership from international and consulting-style environments.
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