Julian S.

Key Skills

Software

Don't disclose

Top Subject Matter

Mechanical Engineering

Computational Methods

Fluid Mechanics

Top Data Types

Audio

Text

Document

Top Task Types

Evaluation/Rating

Computer Programming/Coding

Freelancer Overview

While my background is in mechanical engineering rather than data labeling specifically, the core of that work — judging whether a solution is correct, scrutinizing its assumptions and constraints, and scoring it consistently against a defined standard — is what I do every day. I'm fluent in the Python scientific stack (NumPy, Pandas, SciPy) for writing and checking reference solutions, and my engineering judgment lets me catch the subtle errors that appear when reasoning is internally confident but physically or mathematically wrong. Holding results to clear, code-verifiable acceptance criteria and domain-appropriate tolerances is second nature to me. A few things set me apart. As a Graduate Engineer at Paterson & Cooke, I run hydraulic-transient and pipe-stress analyses on industrial pipelines to standards like ASME B31.3, so I can ground problems in genuine professional practice. In a recent graduate project, I built a fluid–structure-interaction solver in Python (DOLFINx/FEniCSx) and validated its output against analytical reference solutions within quantitative tolerances — pinpointing exactly where the model's built-in assumptions broke down. And earlier, as a test engineer, my job was literally to define acceptance criteria and grade hardware pass/fail against them. That combination of real-world engineering, computational depth, and a structured evaluation background is what would make me effective at producing and assessing high-quality engineering, programming, and math content.

Education

Work History