Data Scientist
Alliance is the leading crypto accelerator and founder community that helps crypto and AI startups reach escape velocity. They offer $500k in funding with interview invites within two weeks and immediate funding upon admission.
Funding
Projects
About Alliance
Alliance runs a structured accelerator program with a 2‑week in‑person onboarding in New York City followed by an 8‑week fully remote program, culminating in a Week 10 Demo Day back in New York where founders present to leading crypto VCs, angels, and experts. The program provides mentorship, weekly check‑ins, live lectures on building and growing in crypto, community forums and founder perks, Demo Day preparation to refine narrative and pitch, and graduation into Alliance DAO, a select community of crypto founders. They highlight funding support ($500k upon admission) and typical fundraising outcomes (the median startup raises $3.5M at a $25M post‑money valuation, often from leading VCs such as Paradigm, Multicoin, and Dragonfly). The FAQ notes that all crypto startups can benefit—from early‑stage teams needing customer development and product strategy to later‑stage teams seeking help with token economics, regulations, and go‑to‑market—while expanding networks and accessing top‑tier mentors and peers.
Skills
About the Role
You own data science and analytics end-to-end, turning ambiguous questions into analysis, models, internal tools, and production systems. You build production Python systems for data collection, enrichment, scoring, and AI-assisted research across internal and external data sources. You develop and improve predictive models, defining features, building evaluation datasets, running experiments, catching leakage and data-quality issues, and moving successful work from research into reliable production releases. You write SQL and own reporting, including dashboards, recurring reports, one-off investigations, and reconciliation against source data. You turn messy data into useful decisions for investing, portfolio support, operations, and growth. You work directly with stakeholders to decide what is worth building, explain findings clearly, and iterate based on how the work is actually used.
Requirements
- Senior, self-directed data scientist or analytics engineer
- Deep experience with Python and SQL
- Strong applied modeling judgment
- Enough data engineering depth to ship your own work
- Clear communicator with good product judgment
- High-agency, entrepreneurial, self-driven
- Comfortable using modern AI tools and LLMs
- NYC-based or willing to relocate
Responsibilities
- Own data science and analytics end-to-end
- Build production Python systems for data collection, enrichment, scoring, and AI-assisted research
- Develop and improve predictive models
- Write SQL and own reporting
- Turn messy data into useful decisions
- Work directly with stakeholders
