← All work
Case StudyTier AOperational2021 — 2022
Iranian Stock Market Screening & Analysis Pipeline
Personal data product that combines multiple Iranian market-data sources into repeatable screening metrics and Excel reports.
DataProductAutomation
Evidence
Practical workflow · 5 users
Context
2021 — 2022 · Operational personal data product · Maturity: Operational.
Problem
Manual screening across multiple data sources was slow and inconsistent.
Users
Five family members using generated reports for practical screening.
My Role
Personal data-product design and implementation.
Product Decisions & Responsibilities
- Defined screening outputs and report structure around practical questions rather than raw data dumps.
Technical Approach
- Built Python/pandas ingestion, time-series metrics, multi-source processing, and Excel reporting.
PythonpandasMarket-data sourcesTime-series analysisExcel
Constraints
- Market data quality/availability.
- The tool was for analysis, not prediction.
Product Flow
- Collect sources
- Normalize/time-align
- Calculate metrics
- Apply screening rules
- Export Excel report
Outcome
- Reports were used by 5 family members in a practical workflow.
What I Learned
- Useful data products translate metrics into repeatable decisions while preserving uncertainty.
Evidence Boundary
What this does — and does not — prove
Not a price-prediction system, trading signal, or investment recommendation.
Next Iteration
Extend the product only after the next decision can be tied to stronger user, operational, or business evidence rather than adding features for their own sake.