обновлено 5 дней назад
Principal Data Scientist, Analytics (AI)
193 500 - 227 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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
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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