Job Description
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Company Overview
The company is a technology-focused organization dedicated to helping small businesses manage essential operations such as payroll, health insurance, retirement benefits, and human resources. With teams across Denver, San Francisco, and New York, the organization supports more than 500,000 small businesses nationwide.
Responsibilities
Lead the Sales Analytics Team
- Establish the vision and direction for a team of data scientists and analysts supporting customer acquisition and product expansion.
- Lead the team in delivering measurable business impact.
- Recruit, mentor, and develop a high-performing analytics organization.
- Establish higher standards for statistical fluency, causal thinking, and strategic analysis.
Insights and Recommendations
- Conduct deep-dive analyses to identify revenue drivers, trends, and anomalies.
- Translate complex analytical findings into clear and actionable recommendations.
- Present insights to senior leadership and cross-functional stakeholders.
- Apply rigorous analytical methods to complex business questions.
Rebuild the Data Foundation
- Partner with Data Engineering and Service Platform teams to modernize foundational data systems.
- Assess existing infrastructure and identify technical debt and scalability challenges.
- Develop and execute a phased roadmap for improving the Sales Data ecosystem.
- Establish scalable systems that support advanced sales analytics and forecasting.
Partner with Key Stakeholders
- Work closely with senior revenue leadership, Sales Operations, Data Engineering, and Service Platform teams.
- Align stakeholders around shared data, infrastructure, and analytics priorities.
- Communicate technical trade-offs and infrastructure requirements clearly to business and technical audiences.
Evolve Forecasting Capabilities
- Improve sales forecasting methodologies through more rigorous analytical techniques.
- Incorporate approaches such as propensity scoring and improved seasonality controls.
- Develop forecasting processes that provide stronger visibility into revenue performance and future trends.
Enable Self-Service Analytics with AI
- Leverage AI-first development approaches to create self-service analytics capabilities for operational teams.
- Identify emerging AI tools that can improve the efficiency and accuracy of revenue analytics.
- Help define how analytics teams can operate effectively as AI and automation increasingly handle routine reporting and data requests.
Drive Team Excellence
- Build and maintain a proactive, high-performing analytics team.
- Shift the team’s focus from reactive query fulfillment toward strategic analysis.
- Define expectations for analytical excellence as AI and automation reduce routine reporting workloads.
- Coach team members to strengthen statistical reasoning, causal analysis, and business judgment.
Connect the Broader Data Organization
- Identify opportunities where Data Engineering, Analytics Engineering, Data Science, or AI/ML Engineering can provide deeper technical solutions.
- Bring the appropriate technical partners into revenue analytics initiatives.
- Encourage collaboration across data and engineering functions to accelerate revenue-focused analytical capabilities.
Qualifications
- 10+ years of experience in data science or a related analytical field.
- 4+ years of experience leading and developing a growing analytics team.
- Demonstrated leadership experience combined with a hands-on builder mindset.
- Ability to step into technical details when necessary, including building reports, conducting analyses, and troubleshooting data issues.
Disclaimer
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