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Senior Manager, Pricing Analytics & Data Science

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  • Software Engineering
    • California - San Francisco
  • Full time
  • JR296410
  • California Salary $200,800 - $276,100
  • Washington Salary $184,000 - $253,000

Description

About the Role: We are seeking a highly skilled and experienced Senior Manager, Pricing Analytics & Data Science to lead our efforts in driving data-driven pricing strategies and answering critical business questions that shape our company's future. This role demands a blend of deep analytical expertise, data science capabilities, exceptional project management skills, and a strong understanding of pricing and packaging within a dynamic SaaS environment. The ideal candidate will be a strategic thinker, skilled problem-solver, and collaborative leader, capable of managing complex analytical projects that directly impact revenue growth and customer success.

Responsibilities:

Please note that this is an individual contributor role.


1. Strategic Pricing Analytics & Data Science:

  • Apply expert-level data analysis, statistical modeling, and machine learning techniques to identify pricing opportunities and optimize revenue
  • Develop and maintain sophisticated pricing models, predictive algorithms, and causal inference models
  • Apply advanced statistical techniques to answer complex business questions (for example: effectiveness of new revenue models, impact of consumption flywheel on future purchases, etc.)
  • Utilize data storytelling to communicate complex analytical findings and recommendations to senior leadership
  • Build consumption prediction models and customer behavior analytics to drive pricing strategy

2. Data Visualization and Reporting:

  • Design and develop industry-standard dashboards using Tableau, ensuring data accuracy and clarity
  • Create compelling data visualizations that effectively communicate key insights from complex statistical analyses
  • Build automated reporting systems for pricing KPIs and business impact metrics
  • Develop executive-level reporting on pricing model performance and strategic initiatives

3. Project and Portfolio Management:

  • Lead complex pricing analytics and data science projects, from hypothesis formation and planning to execution, risk assessment, and resolution
  • Develop and manage a portfolio of pricing initiatives, aligning with long-term strategic goals
  • Break down complex analytical projects into manageable phases, ensuring timely and efficient execution
  • Collaborate with pricing strategy, product, finance, and sales teams to implement data-driven pricing recommendations

4. Data Engineering Collaboration & Technical Leadership:

  • Collaborate with data engineering teams to ensure data integrity and availability for advanced analytics
  • Provide guidance and expertise on data warehousing, ETL processes, and data orchestration
  • Lead technical discussions on analytical approaches and methodology with cross-functional teams

5. Stakeholder Management and Strategic Communication:

  • Build and maintain strong relationships with cross-functional teams, including product management, GTM, sales, finance, business technology, deal desk, and other analytics teams
  • Present statistical findings and model results to executive leadership in clear, compelling narratives
  • Drive consensus on pricing strategy through data-driven recommendations and impact quantification

Qualifications:
Required:

  • Expert-level proficiency in SQL for complex data manipulation and analysis
  • Expert-level proficiency in Tableau Desktop and Cloud for advanced data visualization
  • Strong statistical analysis and modeling skills
  • Experience with predictive modeling and machine learning techniques
  • Advanced business analysis skills with ability to translate business questions into analytical frameworks
  • Advanced project management skills for complex analytical initiatives
  • Experience with pricing and packaging within a SaaS environment
  • Experience with data engineering concepts (data warehousing, ETL, orchestration)
  • Experience with stakeholder and partner collaboration
  • Experience with complexity resolution and portfolio management
  • Experience with handling ambiguity and constant change
  • Strong problem-solving skills with ability to design analytical approaches for ambiguous business questions

Preferred:

  • Advanced proficiency in Python or R for statistical modeling and machine learning
  • Experience with consumption-based pricing models and usage analytics
  • Advanced degree (Master's/PhD) in Statistics, Economics, Data Science, or related quantitative field

For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

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Equal Opportunity Statement.

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Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

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