Senior Data Scientist

Senior Data ScientistLocation: NYC (onsite only – not remote)

Alliance is the leading accelerator for crypto & AI founders. Since 2020 we’ve backed 300+ startups (Rain, Pump, Synthetix, Pendle, and many more), now collectively valued at $15B+.

We’re hiring a Data Scientist to join our in-house engineering team. You’ll report directly to Carter (CTO) and will be responsible for owning features from the requirements definition stage to production.

What You’ll Do

• Own data science and analytics end-to-end: turn ambiguous questions into analysis, models, internal tools, and production systems without waiting on a PM or a large engineering team.
• Build production Python systems for data collection, enrichment, scoring, and AI-assisted research across internal and external data sources.
• Develop and improve predictive models: define features, build evaluation datasets, run experiments, catch leakage and data-quality issues, and move successful work from research into reliable production releases.
• Write SQL and own reporting including dashboards, recurring reports, one-off investigations, and reconciliation against source data.
• Turn messy data into useful decisions for investing, portfolio support, operations, and growth. The output should be understandable and actionable, not just statistically interesting.
• Work directly with stakeholders to decide what is worth building, explain findings clearly, and iterate based on how the work is actually used.

What we’re looking for

• Senior, self-directed data scientist or analytics engineer who can take a loosely defined business problem from first query through a production-quality answer.
• Deep experience with Python and SQL; comfortable working across notebooks, application code, APIs, and Metabase.
• Strong applied modeling judgment: feature design, evaluation, missing data, leakage, calibration, interpretability, and knowing when a simple approach is better.
• Enough data engineering depth to ship your own work: build pipelines, integrate APIs, debug bad source data, and maintain production workflows without heavy engineering support.
• Clear communicator with good product judgment who can work directly with non-technical stakeholders and turn analysis into a recommendation or operating tool.
• Extremely high-agency, entrepreneurial, self-driven.
• Comfortable using modern AI tools and LLMs for analysis, enrichment, evaluation, and automation without treating model output as ground truth.