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3 часа назад

Manager 2, Data Science (Customer Success - Analytics)

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

Текст:
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TL;DR

Manager 2, Data Science (Customer Success - Analytics) (Fintech): Lead data science team generating insights for Services (Payments, Payroll, Lending) and Mid-Market IES platform, measuring customer experiences, funnel health, adoption, and retention using AI+HI strategy. Focus on experimentation, predictive churn models, customer health scores, causal inference, and data-driven recommendations for business strategy and GTM decisions.

Location: Mountain View, California; San Diego, California; San Francisco, California

Company

Global financial technology platform powering prosperity for 100 million customers worldwide with products like TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

  • Build, lead, and mentor data science team across Services and Mid-Market, growing technical and business skills.
  • Define data strategy for funnel health, product adoption, retention, and opportunities in QBO Advanced, IES, HCM, and Money.
  • Lead measurement and experimentation for expert programs, capturing value of human expertise in adoption and confidence.
  • Partner with Customer Success to evolve Customer Health Score with predictive models and next-best-action recommendations.
  • Generate insights for partner-led growth, onboarding, and customer health.
  • Translate business problems into analytical projects, provide recommendations to leaders, and build metrics framework including NRR and tNPS.
  • Apply advanced ML, statistical methods, and A/B testing; champion data-driven innovation.

Requirements

  • BS/MS/PhD in Statistics, CS, Applied Math, Econometrics, Operations Research, or related.
  • 8+ years as data scientist, analyst, or data-driven leader with business impact.
  • Advanced SQL, Python, R, data visualization tools.
  • Expertise in experimentation, predictive modeling, ML, or statistical analysis.
  • Strong collaboration, communication to influence decisions.
  • End-to-end data science solutions creating value.
  • Strategic thinking with hands-on execution in ambiguous environments.

Culture & Benefits

  • Competitive compensation with pay-for-performance, cash bonus, equity rewards.
  • Strong benefits package per applicable plans.
  • Win-together collaboration, challenging status quo.
  • Data-driven innovation culture.

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