You will get clean, validated research data with a reproducible Python report
Project details
Receive a clean, analysis-ready dataset plus a transparent record of what changed. I check types, missing values, duplicates, ranges, joins, and consistency rules, then deliver reproducible Python work and a concise QA report. This is designed for research and technical teams that need defensible results, not a black-box spreadsheet cleanup.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$350
|
Standard
$650
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 1 | 1 |
Frequently asked questions
About Hryhory
Scientific Python Audits | Computational Chemistry PhD
Strasbourg, France - 5:11 am local time
You receive an execution map, reproducibility check, prioritized risk report, and—when included—bounded fixes. I review data flow, dependencies, tests, determinism, provenance, and failure handling across Python, Bash, Jupyter, HPC, and computational-chemistry workflows.
I am a computational chemistry PhD, Head of Physics, Marie Skłodowska-Curie fellow, and published researcher with experience in molecular simulation, free-energy methods, QM/MM, virtual screening, active learning, and quantum chemistry.
Best fit: research teams, biotech/CADD groups, and technical founders who need a defensible workflow review. Start with a repository snapshot, run instructions, and one representative non-confidential input.
Steps for completing your project
After purchasing the project, send requirements so Hryhory can start the project.
Delivery time starts when Hryhory receives requirements from you.
Hryhory works on your project following the steps below.
Revisions may occur after the delivery date.
Profile the data and validation rules
Inspect types, missingness, duplicates, ranges, joins, and consistency rules; confirm tier scope.
Build the reproducible cleanup
Implement and test the Python transformations, preserving a transparent issue and change log.