Anika Rosenzuaig
Data Science & Analytics Leader. I excel at leading data teams to develop strategies that turn complex data into business value. This is my professional portfolio.
My Core Expertise
My work is focused on three key pillars to deliver business value across the entire data lifecycle.
I design and implement modern data platforms (GCP, AWS) using best-in-class tools like dbt and Airflow, building scalable foundations for data-driven organizations.
I leverage predictive modeling and modern AI applications (GenAI/RAG) to uncover new business opportunities and create a competitive advantage.
I perform deep analysis of user behavior and market data to inform product roadmaps, pricing strategies, and go-to-market decisions.
Articles & Case Studies
Here are some examples of how I solve real-world business problems using data.
The Ultimate Guide to A/B Testing Statistics: From Theory to Practice
Go beyond p-values. This deep dive covers everything from choosing the right statistical test for your metrics to calculating sample size with power analysis. A complete guide for data-driven professionals in e-commerce, marketing, and product.
Manual Predictions & Backpropagation in a 2–2–1 Neural Network (Sigmoid + MSE)
A full, step-by-step walkthrough that computes a 2–2–1 neural network by hand: forward pass, MSE loss, formal objective, dependency map, backpropagation derivations, and one complete weight update—ready-to-learn math with concrete numbers.
The Strategic Imperative of RAG: An Investment Framework for Unlocking Enterprise Knowledge
Generative AI is a transformative platform, but its true enterprise value is unlocked when grounded in proprietary data. This analyst report provides a strategic framework for investing in Retrieval-Augmented Generation (RAG), detailing the technology, a portfolio of high-ROI use cases, and a phased roadmap for implementation. RAG is not an experiment; it is a critical investment in building a durable competitive moat.