Privacy Policy & Data Protection
At Huwaya.com, true salary transparency requires absolute anonymity. Discover how our zero-PII architecture safeguards your identity.
1. Information We Never Collect (Zero-PII Standard)
Huwaya.com is engineered to operate without collecting Personally Identifiable Information (PII). Under no circumstances do we require, record, or store:
2. Structural Market Data We Collect
To calculate accurate market percentiles (25th, 50th median, 75th percentiles) and generate regional job analysis reports across Iraq, we collect non-identifying operational parameters:
- Role Information: Job Title, Industry Sector, and Years of Professional Experience.
- Compensation Data: Gross Monthly Base Salary, Currency (IQD or USD), and Additional Benefits (e.g. Health Insurance, Annual Bonus, Housing Allowance).
- Geographic Region: Governorate / City (e.g. Baghdad, Erbil, Basra, Sulaymaniyah, Mosul).
- Workplace Culture Feedback: Ratings on Work-Life Balance, Compensation Fairness, Career Growth, Management Quality, and Overall Culture.
3. Cryptographic Hashing & Anti-Spam Security
To prevent duplicate submissions, spamming, and automated manipulation while maintaining strict user privacy, Huwaya.com uses a one-way cryptographic hash (`HMAC-SHA256`) derived from your connection metadata.
This one-way hash acts solely as an anonymous rate-limiting token (e.g. limiting users to 1 salary entry per 90 days). It is impossible to reverse-engineer this hash into an IP address or personal identity, and it is stored in a separate Firestore collection disconnected from your salary record.
4. Cookies & Advertising (Google AdSense)
Huwaya.com uses standard essential cookies to remember user preferences (such as light/dark mode and active currency selections).
We also integrate Google AdSense (`ca-pub-1990800372543748`) to serve advertisements. Google uses cookies to serve ads based on your visit to Huwaya.com and other websites on the Internet. Users may opt out of personalized advertising by visiting Google's Ad Settings.
5. Machine Learning & AI Model Training
Aggregated, anonymized salary figures are utilized to train Machine Learning models (such as XGBoost wage prediction algorithms) and feed Large Language Model (LLM) RAG indexing datasets (`/llms.txt`). No individual submission contains identifying details capable of exposing personal identity to AI systems.
6. Data Retention & Rights
Anonymized salary records and workplace reviews are retained indefinitely to build long-term labor market trend lines for Iraq. Because submitted entries are entirely unlinked from personal identities, individual deletion requests cannot be tied to a specific submission once recorded.