15 часов назад
Principal Data Scientist, Platform Monetization (AI)
197 300 - 313 700$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Data Scientist, Platform Monetization (AI): Leading data science for Slack's platform monetization strategy, analyzing how developers and users build and engage with agents and each other with an accent on product growth, customer adoption, and go-to-market performance. Focus on designing experimentation and measurement strategies, building scalable analytical foundations, and influencing topline decisions through statistical analysis, predictive modeling, and deep-dive insights.
Location: California - San Francisco, United States
Salary: $197,300–$313,700 annually. In select cities within the San Francisco and New York City metropolitan areas: $237,000–$344,700 annually.
Company
is a workplace platform within Salesforce that enables users to customize workflows, integrate everyday tools, and collaborate with agents and each other.
What you will do
- Lead data science efforts supporting 's platform monetization strategy and execution.
- Partner with Product, Sales, Finance, business strategy, and go-to-market stakeholders to identify opportunities and influence strategic decisions.
- Apply statistical methods, experimentation, segmentation, forecasting, and deep-dive analysis to understand customer behavior, adoption, growth, and user journeys.
- Design measurement strategies and success metrics for products, programs, and strategic initiatives.
- Partner with Data Engineering to develop trusted datasets and scalable analytical foundations for modeling and experimentation.
- Set the data science vision, prioritize roadmaps, and coach and mentor team members.
Requirements
- 7+ years of experience in product data science in related technology industries.
- Strong record of using data to drive product teams and influence company-level outcomes.
- Advanced SQL and proficiency in at least one data science programming language, such as Python, R, or Scala.
- Strong foundation in statistics, experimentation, causal inference, predictive modeling, and analytical problem solving.
- Experience with large-scale data technologies such as Spark, Presto, Hive, Hadoop, or similar distributed platforms.
- Ability to communicate complex analytical findings clearly to executive and cross-functional audiences.
Nice to have
- 2+ years of experience in a product data science technical lead or managerial role.
- Knowledge of workflow orchestration tools such as Apache Airflow.
- BS degree in a quantitative field; an MS or PhD in a quantitative field is a strong plus.
Culture & Benefits
- Collaborative, diverse, supportive, and inclusive work culture.
- Medical, dental, vision, mental health support, and life and disability insurance.
- Paid parental leave and time-off programs.
- 401(k) and employee stock purchasing program.
- Reasonable accommodations are available during the application and recruiting process.
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