6 часов назад
Data Scientist (Customer Success)
117 000 - 158 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (Customer Success) (Business Tax Analytics): Measuring and optimizing expert-led customer experiences for the Business Tax product with an accent on experimentation, causal inference, predictive modeling, and KPI development. Focus on designing A/B tests, identifying customers who benefit from expert engagement, integrating AI-assisted workflows, and translating complex data into strategic recommendations.
Location: San Diego, California, United States
Base pay: $117,000–$158,500 annually; the position may also include a cash bonus, equity rewards, and benefits.
Company
is a financial technology platform serving approximately 100 million customers through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.
What you will do
- Measure how expert-led customer initiatives affect filing behavior, product adoption, retention, deductions guidance uptake, and customer lifetime value.
- Develop strategic recommendations on expert capacity and Business Tax investments using multiple data sources.
- Define KPIs, standardized metrics, reports, and dashboards for the Business Tax expert experience.
- Design, execute, and analyze A/B tests and other experiments involving engagement timing, channels, and content.
- Build predictive models to identify customers most likely to benefit from expert engagement and uncover growth opportunities.
- Collaborate with product, expert operations, marketing, customer support, data engineering, and AI teams to improve measurement and decision-making.
Requirements
- 4+ years of experience in product, customer care, customer experience, or applied analytics, ideally involving expert-assisted or high-touch services.
- Advanced SQL and big data experience with technologies such as Redshift, Spark, Hive, BigQuery, or Databricks.
- Experience with BI and visualization tools such as Tableau, Qlik, or Dash.
- Deep expertise in experimentation design and causal inference methods, including A/B/n testing, bandits, propensity scores, difference-in-differences, and synthetic controls.
- Understanding of AI-native architectures and GenAI platforms, with strong business acumen, data storytelling, communication, and cross-functional collaboration skills.
- Bachelor’s degree in a quantitative field such as Engineering, Data Science, Statistics, Mathematics, Computer Science, or Economics; a master’s degree is preferred.
Nice to have
- Qlik certification.
- Master’s degree in a related quantitative field.
Culture & Benefits
- Fast-paced environment with flexibility to shift priorities.
- Competitive compensation with pay-for-performance rewards.
- Potential cash bonus, equity rewards, and benefits according to applicable plans.
- Collaboration across technical, business, product, operations, marketing, support, engineering, and AI functions.
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