Risk Intelligence Analyst Jobs in Raleigh, NC (NOW HIRING)

Job Summary
The Academy -GTM Business Analyst & Business Intelligence role sits at the center of our Cloud Customer Success data transformation. You will work directly with the Director of Strategy & Operations to architect and operationalize the GTM Data Engine, a connected intelligence system that links the full customer lifecycle across all Cloud products, enabling CS leaders and field teams to make faster, more confident, data-driven decisions. This is a builder role. You will be responsible for designing the data foundation, surfacing actionable insights, and embedding AI-powered systems that scale customer success strategy, operational planning, and performance management across the entire organization.
Responsibilities
Data Engine Architecture & Foundation
- Partner with the Director of Strategy & Operations to define the end-to-end architecture of the GTM Data Engine
- Connect sales, CS, RevOps, and product usage data across Cloud product offerings
- Design and maintain scalable data models, taxonomies, and pipelines supporting customer health scoring, risk analysis, migration tracking, and KPI metrics
- Establish a single source of truth for CS performance data to eliminate fragmented reporting across tools and teams
- Lead data governance practices including definitions, lineage, quality standards, and access controls
Business Intelligence & Reporting
- Build and own executive-ready dashboards (MBRs, QBRs, board-level views) using tools like Power BI and Salesforce reports
- Develop self-serve reporting frameworks to enable leaders to access insights independently from the data team
- Translate complex datasets into clear narratives by visualizing trends, identifying anomalies, and linking metrics to strategic outcomes
- Own KPI tracking for customer success performance indicators including CSAT, migration velocity, time-to-value, digital engagement, and 1:many coverage ratios (team productivity)
AI-Powered Systems & Automation
- Leverage AI tools such as Copilot, Gemini, NotebookLM, and Cursor to accelerate data analysis, insight generation, and documentation workflows
- Build AI-assisted playbooks, scoring models, and alert systems to proactively identify at-risk accounts, expansion signals, and migration blockers
- Design and implement prompt engineering frameworks for repeatable, AI-augmented analytics workflows
- Partner with CS leadership to identify automation opportunities in operational processes and integrate AI into MBR/QBR preparation cycles
Strategic Analysis & Operational Planning
- Conduct deep-dive analyses supporting FY planning cycles, headcount modeling, coverage model design, and GTM segmentation decisions
- Support in preparing executive presentations, strategy decks, and cross-functional deliverables by translating data into executive-ready storylines
- Monitor leading indicators and provide forward-looking analysis to enable proactive CS operations rather than reactive reporting
- Serve as the intelligence layer for cross-functional partners including Sales, RevOps, BA/BI, Product, and IT
Cross-Functional Collaboration & Stakeholder Enablement
- Act as the embedded data partner for CS leaders across all BUs
- Understand their business context and translate operational questions into analytical solutions
- Collaborate with RevOps and BA/BI teams on data infrastructure alignment, architecture decisions, and tool integrations
- Facilitate working sessions to define business requirements, validate metric definitions, and align stakeholders on data standards
- Mentor CS team members on data literacy, self-serve tooling, and evidence-based decision making
SKILLS & QUALIFICATIONS
- Advanced SQL, BI, and data visualization expertise
- Experience with data warehouses, ETL tools, and Salesforce ecosystems
- Proficiency in Python/R, Excel, and AI-enabled analytics
- Ability to build dashboards, automate insights, and drive self-service reporting
- Strong executive communication and data storytelling skills through presentations and strategic recommendations
Education

• Demonstrated experience building analytics products or data systems from the ground up (not just maintaining existing infrastructure)
• Experience working directly with senior leadership and presenting data-driven recommendations
• Prior exposure to Customer Success or post-sale functions is strongly preferred; understanding of SaaS customer lifecycle and renewal economics is a plus
• Bachelor's degree in Business, Economics, Statistics, Computer Science, or a related quantitative field; MBA or advanced degree a plus

Compensation:
The target salary range for this position is 113,050 - 168,300 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. The range is based on 'On Target Earnings' (OTE) representing the total potential earnings, which is the sum of the base salary and potential commission earned when performance targets are achieved. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off (PTO), various Leave options, employee stock purchase plan, and/or restricted stocks (RSU's). These offerings are subject to regional variations and governed by local laws, regulations, and company policies. We will provide detailed information about the specific benefits for your region during the recruitment process.