Data Analytics Lead (AI)

Location: Hybrid in San Francisco or Barcelona, United States or Spain

Company

hirify.global builds infrastructure for enterprises to create and orchestrate autonomous AI workforces across voice, email, and enterprise systems, with roots in logistics and a platform developed in Y Combinator.

What you will do

• Define and track product, feature, and AI agent metrics.
• Design, run, and interpret A/B tests for models, prompts, agent behavior, workflows, and product features.
• Measure agent performance against task completion, operational efficiency, response quality, automation rates, and customer outcomes.
• Connect offline model evaluations with production performance and analyze conversations, workflows, and product usage.
• Investigate anomalies and regressions, perform root-cause analyses, and recommend improvements.
• Build statistical models, simulations, dashboards, self-serve tools, and analytical frameworks while improving instrumentation and data quality with Engineering.

Requirements

• 4+ years of experience in Data Science, Product Analytics, or another highly quantitative product role.
• Strong experience with experimental design, A/B testing, statistics, causal inference, and hypothesis-driven analysis.
• Advanced proficiency in SQL and Python.
• Experience defining and operationalizing product and feature metrics.
• Ability to turn ambiguous product questions into rigorous analyses and actionable recommendations, distinguishing statistical significance from meaningful product or customer impact.
• Experience partnering closely with Product, Engineering, or Machine Learning teams.
• Strong written and verbal communication skills, attention to detail, and commitment to analytical accuracy.
• Founder mindset demonstrated through ownership, independence, curiosity, and willingness to investigate problems deeply.

Nice to have

• Experience with large language models, AI agents, generative AI, or other probabilistic ML products.
• Experience measuring production impact from model, prompt, retrieval, or orchestration changes.
• Familiarity with ML evaluation systems and relationships between offline evaluations and online metrics.
• Experience analyzing conversational, NLP, speech, or other unstructured data.
• Experience with enterprise or B2B products and with combining quantitative analysis and qualitative methods.
• Familiarity with modern analytics infrastructure, data warehouses, experimentation platforms, and business intelligence tools.
• Prior experience in a fast-growing startup or another highly ambiguous environment.

Culture & Benefits

• Ownership and autonomy over projects with encouragement to ship.
• Operating principles emphasize extreme ownership, craftsmanship, kindness, urgency with focus, meritocracy, talent density, and first-principles thinking.
• Healthcare, dental, and vision coverage.
• Competitive salary and equity in a high-growth startup.