Full-stack Data Scientist (co-founder) (equity only - no compensation)

Job Title: Full-Stack Data Scientist
Location: Remote
Type: Equity-Based (Pre-funding)
Commitment: 20–25 hours/week

About Us
NPPD CARE is building a category-defining mobile-first wellness intelligence ecosystem. Our mission is to revolutionize how people manage physical, emotional, spiritual, and lifestyle health — using conversational AI, data-driven personalization, and behavioral science. We are not building another app — we’re building a human operating system.

Role Overview
As a Full-Stack Data Scientist, you will be responsible for designing, building, and optimizing the end-to-end data pipeline — from collection (voice, chat, wearable data, behavior) to modeling (emotion, habits, wellness scoring) to insights delivery (recommendations, nudges, forecasts). You will work directly with product, AI, and mobile teams to make wellness predictive, adaptive, and intelligent.

Responsibilities
1. Data Architecture & Infrastructure
Design and maintain data models for 12+ wellness domains across emotional, behavioral, physical, and environmental dimensions

Build scalable data pipelines (structured + unstructured) from user inputs (text, audio, biometric, in-app behavior)

2. AI & Behavioral Modeling
Develop algorithms for wellness scoring, habit prediction, and emotional state estimation

Build multimodal models using NLP, voice data (speech-to-text + tone), wearables, and app interaction

Work closely with AI team to integrate custom LLM/ML components (chat, recommendations, anomaly detection)

3. Experimentation & Insights
Design A/B tests for product features (e.g., nudges, streak systems)

Create real-time dashboards and behavioral heatmaps for internal teams

Define and monitor product-level KPIs (engagement, retention, mood delta, ritual compliance, etc.)

4. Privacy-First Data Practices
Implement data governance strategies aligned with HIPAA/GDPR

Ensure all models and data handling respect user anonymity and emotional safety

Requirements
Must-Have:
3–5 years of experience in data science (consumer tech or wellness domain preferred)

Full-stack DS capabilities — data engineering, modeling, interpretation, deployment

Proficiency in Python, SQL, TensorFlow/PyTorch, ML pipelines

Strong grasp of behavioral data and emotional analytics

Experience with NLP (especially sentiment/emotion detection)

Ability to work with product, mobile, and AI/LLM teams collaboratively

Good-to-Have:
Experience with voice or audio signal processing

Experience with wearable integrations (Apple HealthKit, Fitbit API)

Exposure to health, wellness, or psychological data modeling

Familiarity with federated learning or privacy-first ML

You Should Be Someone Who:
Thinks of data as a living system, not just numbers

Can map emotion, behavior, and context like an ecosystem

Knows when to simplify and when to go deep

Doesn’t wait for “perfect data” — builds with messy signals

Wants to build a product that actually changes lives

What You Get:
Core team equity in a category-defining venture

Ownership of the intelligence backbone of the product

The opportunity to shape how wellness is understood by machines

A founder-level seat in defining emotional AI at scale