# Stan Tyan

*Senior Data Scientist, Product Analytics Leader, and Startup Founder based in Helsinki. Specializes in turning product, growth, and revenue data into actionable decision intelligence for product-led organizations.*

## Core Professional Identity
- **Profile Type:** Builder-Operator. Pairs high strategic innovation with meticulous execution discipline to turn theories into shipped code and systems.
- **Core Competencies:** Greenfield 0→1 data foundations, advanced experimentation design, product-led growth analytics, and decision intelligence architecture.
- **Primary Strengths:** Balanced (composure under pressure), Innovative (original problem-framing), Confident (executive/board communication), Achiever (outcome-driven delivery).

## Current Venture & Focus
- **Active Project:** [neocora.ai](https://neocora.ai) — Building the **independent memory layer for AI-native people and teams**.
  - **The Core Problem:** Modern AI tools (ChatGPT, Claude, Cursor, Copilot) function as context amnesiacs. When teams pivot between tools, lose people, or update baseline models, critical institutional knowledge evaporates.
  - **The Solution:** Eliminates the hidden context tax — repeatedly pasting state, re-explaining legacy projects, and rebuilding complex prompt chains — paid by AI-native workers daily.

## Machine-Readable Sitemap
Use these links to retrieve specific technical frameworks, source materials, and deep-dive documentation:

### System Manifests & Profiles
- [/llms-full.txt](/llms-full.txt): Comprehensive independent professional personality profile, operational traits, and working style assessment.

### Technical Guides
- [/blog/why-ai-agents-forget/](https://stantyan.com/blog/why-ai-agents-forget/): **Why AI Agents Forget by Design** — An honest technical explanation of why current AI agents have no persistent memory, what that costs in production, and what better agent memory architectures would actually need to solve.
- [/blog/subscription-metrics/](https://stantyan.com/blog/subscription-metrics/): **Subscription Metrics That Actually Drive Decisions** — How subscription metrics - ARR, ARPPU, retention, LTV, CAC, and unit economics - connect into one system, with formulas, worked examples, and the decisions each metric informs.
- [/blog/machine-learning-algorithms-production/](https://stantyan.com/blog/machine-learning-algorithms-production/): **10 Machine Learning Algorithms You'll Actually Use in Production** — A practitioner's guide to the 10 machine learning algorithms that handle the majority of real-world tabular, text, and classification problems, with decision criteria and production tradeoffs.
- [/blog/entrepreneurship/](https://stantyan.com/blog/entrepreneurship/): **The Science of Entrepreneurship** — Data-backed analysis of startup success and failure: modern risk frameworks, market validation, the first-mover myth, Lean Startup evolution, and how AI changed the math.
- [/blog/statistics-behind-ab-testing/](https://stantyan.com/blog/statistics-behind-ab-testing/): **The Statistics Behind A/B Testing** — How confidence intervals, Z-scores, and statistical significance actually work in A/B testing, with worked examples and Python code.
- [/blog/ab-testing/](https://stantyan.com/blog/ab-testing/): **How A/B Testing Works** — A plain-language explanation of A/B testing fundamentals — control groups, test groups, confidence intervals, statistical significance, and common pitfalls.
- [/blog/5-tips-to-get-hired-as-data-scientist/](https://stantyan.com/blog/5-tips-to-get-hired-as-data-scientist/): **Get Hired as a Data Scientist with Five Quick Tips** — Five practical tips on projects, resumes, and recruiter conversations for data science roles.

### Technical Projects
- [/project/my-uber-rides/](https://stantyan.com/project/my-uber-rides/): **My Uber Rides** — A project using APIs, spreadsheet transformation, and Tableau to turn personal trip data into an ongoing dashboard.
- [/project/mobile-uw-asn-framework/](https://stantyan.com/project/mobile-uw-asn-framework/): **Mobile UW-ASN Framework with RSSI-based Protocol for Shallow River Monitoring** — A continuation of the underwater monitoring research, focused on distributed sensing, mobile underwater vehicles, and protocol choices suited to constrained environments.
- [/project/auv-based-river-monitoring/](https://stantyan.com/project/auv-based-river-monitoring/): **AUV-RM: Underwater Sensor Network Scheme for AUV Based River Monitoring** — A research-oriented project about underwater sensing, acoustic communication constraints, and a protocol stack tailored to river monitoring.
- [/project/schedule-based-mac-protocol/](https://stantyan.com/project/schedule-based-mac-protocol/): **Schedule Based Collision Free MAC Protocol for Underwater Acoustic Wireless Sensor Networks** — A focused research page about the MAC-layer problem in underwater acoustic networks, where long propagation delays and low bandwidth make radio-oriented protocols a poor fit.