Alexander Kuznetsov is a Data Scientist II based in Madrid with 12 years of software and analytics experience, blending deep ML expertise (uplift, demand prediction, ranking, LTV/churn, dynamic pricing, recsys, credit scoring) with hands-on MLOps and cloud deployment skills. He has driven measurable business impact across retail, RideTech, marketplaces and fintech—improving CTRs, conversion and credit risk metrics—and has applied advanced experimentation methods (switchback, CUPAC, VWE) at scale. Comfortable shipping models to production using Python, TensorFlow, PySpark, Docker/Kubernetes, Airflow and GCP/Databricks, he also experiments with LLMs for NER, RAG and QLoRA tasks such as brand-name matching. A former consultant and startup co-founder, he pairs strategic product thinking with rigorous A/B testing and financial modeling, and uniquely combines a 20+ year software background (Ruby on Rails, Java) with modern data science practice.
12 years of coding experience
4 years of employment as a software developer
Free Courcera cource, Game Theory, Free Courcera cource, Game Theory at Stanford University
Free Courcera cource, Business Analytics, Free Courcera cource, Business Analytics at ESSEC Business School
Master in International Management (MiM), Business Administration, Management and Operations, Master in International Management (MiM), Business Administration, Management and Operations at IE Business School
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