Understand the question
Clarify what a useful answer would actually change, rather than starting with a tool or metric.
About / Federica Iengo
Curiosity, with a method behind it.
I like getting to the bottom of things. That might mean tracing an inconsistency through a dataset, understanding why a search system describes a product in a certain way, or finding a clearer way to explain a complex result.
What I work on
Two fields, one way of thinking.
Data analytics
I use SQL, PostgreSQL, Snowflake, dbt, Python and pandas to explore datasets, test assumptions, reconcile figures and turn analysis into decisions. I care about the path from raw data to a conclusion as much as the conclusion itself.
AI Search and information visibility
My research covers SEO, AEO and GEO: how information is structured, retrieved, cited and presented in generated answers. I build controlled comparisons and document where public evidence ends and interpretation begins.
These interests overlap. Both require clear definitions, reliable sources, repeatable checks and a willingness to change your mind when the evidence changes.
How I approach a problem
Make the reasoning inspectable.
Follow the evidence
Check source quality, definitions and edge cases. Separate what is observed from what is inferred.
Build something repeatable
Document the method so another person can inspect, challenge or extend the work.
Beyond the immediate brief
I learn by looking beneath the surface.
I'm interested in the systems behind the tools we use: how algorithms behave, how information travels and how complex ideas become understandable. That curiosity also takes me into scientific research and emerging technology. I don't treat curiosity as expertise; I treat it as a reason to keep learning.
Explore the work
See the methods in practice.
Projects and research notes include the questions, limitations and evidence behind the work, not just polished conclusions.