Data Scientist, API (AI)

TL;DR

Data Scientist, API (AI): Building measurement systems to improve the API platform's legibility and improveability with an accent on developer adoption, engagement, retention, and platform health. Focus on translating data into product decisions that improve reliability and developer outcomes at scale.

Location: Based in San Francisco and requires three days in the office per week. Relocation assistance is available.

Salary: $293K – $515K

Company

hirify.global is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

What you will do

• Own the core KPI framework for the API platform, spanning developer adoption, engagement, retention, and platform health.
• Build end-to-end funnels that identify where developers succeed or get stuck—from first integration through scaling to production.
• Define and operationalize platform guardrails (e.g., reliability, latency, error rates, cost/efficiency) and connect them to user outcomes.
• Design and evaluate experiments and rollouts to quantify the impact of platform and product changes.
• Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct.
• Translate complex analysis into clear, actionable insights for leadership and cross-functional stakeholders.

Requirements

• 10+ years of experience in data science roles within product or technology organizations (platform or developer-facing experience is a plus).
• Expertise in statistics and causal inference, applied in both experimentation and observational studies.
• Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation.
• Proven experience designing and interpreting experiments and making statistically sound recommendations.
• Experience building datasets, metrics, and data pipelines that power production decision-making.
• Ability to build relationships with diverse stakeholders and cultivate strong partnerships across Product, Engineering, Research, and GTM teams.

Nice to have

• Experience with developer platforms, APIs/SDKs, or usage-based products.
• Experience with platform reliability analytics, incident impact measurement, or performance/cost optimization.
• Familiarity with AI evaluation and quality measurement systems (online/offline evals, human-in-the-loop, safety/quality guardrails).