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Principal Data Scientist, Analytics (AI)

193 500 - 227 500$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Principal Data Scientist, Analytics (AI): Building scalable self-service analytics, data science frameworks, predictive models, and AI-assisted tools for Product and Engineering teams with an accent on product analytics, experimentation, semantic layers, and trustworthy insights. Focus on designing causal and predictive models, architecting model-ready data pipelines, enabling natural-language querying with LLMs, and leading analytical rigor across the organization.

Location: San Francisco, United States

Salary: $193,500–$227,500 annual base compensation

Company

hirify.global is a data collaboration platform focused on consumer privacy, data ethics, identity, and connected customer insights.

What you will do

  • Design and certify reusable self-service metrics, dashboards, analytical products, skills, and AI agents for Product and Engineering stakeholders.
  • Build semantic layers, metric frameworks, data models, and analytical abstractions for AI-assisted insights and natural-language querying.
  • Develop predictive, diagnostic, causal, scenario, and simulation models for product adoption, engagement, retention, and monetization.
  • Own experimentation strategy, including A/B testing, quasi-experiments, and causal inference.
  • Partner with architects and data engineers to build scalable data stacks, model-ready datasets, feature pipelines, and reproducible data science operations.
  • Lead cross-functional analytics initiatives, influence product roadmaps, mentor analysts and data scientists, and present findings to executives.

Requirements

  • MS or PhD in Computer Science, Statistics, Mathematics, or a related field.
  • 10+ years of experience in Data Science and Analytics, delivering product insights and statistical models at scale.
  • Expert-level Python and SQL skills, experience with massive cloud datasets such as BigQuery, and hands-on experience with complex data science and LLM models.
  • Experience building and scaling AI-powered analytics and architecting a modern data science stack.
  • Deep understanding of Product Analytics metrics and concepts, preferably in a SaaS or platform environment.
  • Advanced experience partnering with data engineers and using dbt or similar data modeling frameworks, with a strong focus on rigor and reproducibility.

Culture & Benefits

  • Collaborative environment with cross-functional work across Product, Engineering, and Design.
  • Flexible paid time off, paid holidays, options for working from home, and paid parental leave.
  • Medical, dental, vision, life and disability insurance, employee assistance, and lifestyle benefits.
  • 401(k) matching at a 1:1 rate up to 6% of salary.
  • In-person and virtual events, including game nights, happy hours, camping trips, and sports leagues.

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