обновлено 3 дня назад
Manager 2, Data Science (AI/ML)
189 000 - 256 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Manager 2, Data Science (AI/ML) (Customer Success Analytics): Leading measurement of expert-driven service excellence and developing data models, experimentation frameworks, and decision engines for Intuit's customer success platform with an accent on causal inference, advanced analytics, and workforce optimization. Focus on connecting expert behavior, training, quality, and operational signals to conversion and customer-serving time while leading a team of data scientists.
Location: San Diego, California or Mountain View, California
Salary: $189,000–$256,000 base pay in San Diego, with potential cash bonus, equity rewards, and benefits.
Company
is a global financial technology platform serving customers through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.
What you will do
- Own measurement strategy across expert conversion, operational capabilities, training and upskilling, service quality, guidance adherence, and labor optimization.
- Advance causal inference and controlled experimentation to connect expert behavior and service guidance with conversion and customer-serving time.
- Build cross-signal causal decision engines, metric frameworks, data models, and learning-platform efficacy frameworks.
- Partner with VEP, Expert Network, Service Design, Operations, Service Delivery, Learning & Development, and Expert Engagement leaders on strategy and investment priorities.
- Lead and develop a team of analysts and data scientists while managing short- and long-term analytics projects end to end.
- Improve experimentation rigor, data quality, visualization, analytics workflows, and the data roadmap.
Requirements
- 7+ years of analytics and data science experience, including product analytics and customer or expert experience analytics.
- Proven experience leading analysts or data scientists.
- Hands-on experience with advanced statistical analysis, controlled experimentation, hierarchical mixed-effects A/B testing, and applied data science.
- Experience with causal inference methods such as propensity scores, difference-in-differences, and synthetic control.
- Proficiency with SQL and Python, plus experience applying AI, machine learning, and GenAI tools.
- Bachelor’s or Master’s degree in a quantitative field and strong communication skills with technical and non-technical colleagues.
Culture & Benefits
- Competitive compensation with a pay-for-performance approach.
- Potential cash bonus, equity rewards, and benefits under applicable company plans.
- Opportunity to shape a transformational customer success and expert service platform.
- Cross-functional environment focused on rigorous analytics, learning, innovation, and challenging the status quo.
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