startup-data-scientist

Transform startup user data into validated insights for pivots and growth.

Updated Jan 5, 2026
One-click install
npx skills add https://github.com/rwHiveAqua/advisor --skill startup-data-scientist
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: startup-data-scientist
Source: https://github.com/rwHiveAqua/advisor/tree/main/.claude/skills/startup-data-scientist
Command: npx skills add https://github.com/rwHiveAqua/advisor --skill startup-data-scientist

SYSTEM DOCUMENTATION & REQUIREMENTS

## What problem does it solve? Startup teams often lack a unified way to transform raw user data into actionable decisions. This skill bridges methodology and measurement, aligning Lean Startup practices with data-driven validation.

## Core Features & Use Cases

  • Analytics Implementation: design tracking schemas, set up data pipelines, and create dashboards for core startup metrics.
  • Metrics Analysis & Hypothesis Validation: compute cohort analyses, retention, churn, and conduct experiment result interpretation.
  • Data-Driven Advice: provide evidence-based pivot/persevere recommendations and support customer development.

### Quick Start Ask the skill to draft a minimal analytics plan for a new onboarding flow and outline the first dashboard and metrics to track.

Frequently Asked Questions about startup-data-scientist

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up event tracking and analytics schemas for startup user data?▼

To set up event tracking for startup user data, you need to design tracking schemas and establish data pipelines that capture user interactions across Build-Measure-Learn cycles. This enables accurate measurement of core startup metrics for dashboards.

What metrics should I track for cohort analysis and customer development?▼

For cohort analysis and customer development, you should track retention, churn, and core engagement metrics. These measurements validate user behavior across Build-Measure-Learn cycles and provide evidence-based recommendations for growth.

How do I build dashboards to analyze startup retention and churn using SQL and Python?▼

To build dashboards analyzing startup retention and churn, use SQL, Python or R for data processing, then integrate BI tools. This creates visual reports of cohort analyses and metric measurements for your startup's growth.

Can I use this approach to validate assumptions during a Lean Startup pivot?▼

Yes, you can validate assumptions during a Lean Startup pivot by applying cohort analysis and A/B testing to your user data. This provides evidence-based recommendations on whether to persevere or adjust your strategy.