AI Adoption & Sales Productivity Analyst
New
J
JobgetherSales Operations
Based in the United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 2–4 years
- Required Skills
- SQLBusiness IntelligenceMicrosoft Power BITableauMicrosoft ExcelChange ManagementGoogle SheetsLookerData analytics
Requirements
- Bachelor’s degree in Business, Data Analytics, Information Systems, or a related discipline.
- 2–4 years of experience in sales operations, revenue operations, business analytics, or data analytics.
- Strong working proficiency with Microsoft Excel or Google Sheets.
- SQL experience is considered a significant advantage.
- Familiarity with business intelligence and dashboarding platforms such as Tableau, Power BI, or Looker.
- Understanding of sales processes, workflows, productivity metrics, and go-to-market operations.
- Familiarity with AI-enabled sales technologies like conversation intelligence or sales copilots.
- Demonstrated ability to learn and evaluate new software and technology quickly.
- Experience supporting technology implementations, change-management initiatives, or software rollouts.
- Strong analytical, problem-solving, and project coordination skills.
- Effective stakeholder communication and collaboration skills across cross-functional teams.
Responsibilities
- Track AI tool adoption, usage, engagement, and performance metrics across sales and account management teams.
- Analyze the relationship between AI adoption and business outcomes like productivity, sales cycle time, and win rates.
- Design and coordinate pilots for emerging AI capabilities and gather actionable feedback.
- Identify sales workflow bottlenecks and partner with Revenue Operations to recommend improvements.
- Build and maintain dashboards to provide leadership with visibility into performance trends.
- Support onboarding, training, and change-management activities for new AI technology rollouts.
- Collaborate with IT and vendors on tool configuration, integrations, and ongoing optimization.
- Translate analytical findings into practical recommendations for non-technical stakeholders.
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