I don't have a background in functional programming - and I never set out to write it. But somewhere between writing trait-based epidemiological pipelines, composing data transformations, and leaning hard on Result, enums, and pattern matching, I started hearing from others: 'That's pretty functional.' In this talk, I'll explore what it means to write functional-ish Rust as someone solving real-world scientific problems. I'll walk through the patterns I reach for - like chaining iterators, avoiding shared state, and embracing expressive types - and reflect on which functional programming ideas emerge naturally in Rust, even if you're not trying. I'll also share how designing for epidemiologists - most of whom are used to chaining functions in Python (like Pandas) or R - has pushed me toward creating ergonomic Rust APIs with Python and R bindings. These tools aim to feel familiar to scientists while leveraging Rust's power and safety under the hood. This is a talk for functional programmers curious about Rust, and for Rustaceans wondering if they've been functional all along. No formal theory required - just real code, real use cases, and a pragmatic perspective from someone building public health tools in Rust.