Operations Analytics Lead

Accountabilities

• • Own the analytics portfolio: Translate operations strategy into a prioritized roadmap of data, analytics, and AI opportunities, distinguishing high-value structural problems from lower-impact quick wins.
  • Turn data into decisions: Analyze and interpret operational data, develop compelling narratives, and provide recommendations that help senior leaders make better decisions.
  • Drive adoption and business impact: Ensure insights are embedded into real workflows and decision points, taking ownership of whether analytics solutions are actually adopted and create measurable value.
  • Partner with data and engineering teams: Qualify opportunities for development, define clear requirements, business rules, data dependencies, success criteria, and acceptance standards, and evaluate delivered solutions for accuracy and effectiveness.
  • Shape the operational AI agenda: Identify practical opportunities for AI and agentic capabilities, assess their potential value and limitations, and represent operational needs in AI governance and implementation discussions.
  • Prioritize meaningful outcomes: Focus resources on the most important operational data problems and measure success through changed decisions, improved adoption, and realized business value.
  • Build strong cross-functional partnerships: Work collaboratively with central data teams and operational stakeholders, maintaining shared ownership throughout the lifecycle rather than relying on siloed handoffs.
  • Support continuous improvement: Investigate data discrepancies, challenge assumptions when appropriate, and continuously identify opportunities to improve analytics, reporting, and operational processes.

  Requirements

  • Experience: 8+ years in data product ownership, analytics, data subject matter expertise, or a comparable role, with demonstrated evidence that data initiatives have influenced measurable business outcomes.
  • Operational analytics expertise: Strong understanding of operational data and reporting, including the ability to navigate complex or imperfect data environments and determine what information is most relevant.
  • Analytical judgment: Ability to critically assess data, analytics, and models and translate findings into sound business recommendations without necessarily being responsible for building the underlying models.
  • Cross-functional collaboration: Experience partnering effectively with centralized data and engineering organizations, ideally in an embedded data-owner or business-facing analytics capacity.
  • Communication and influence: Excellent communication skills and the ability to translate complex analysis into actionable decisions, build trust with senior stakeholders, and confidently present an independent point of view.
  • AI fluency: Practical understanding of AI and agentic technologies, including their capabilities, limitations, appropriate use cases, and operational implications.
  • Technical understanding: Working knowledge of modern data ecosystems, including Snowflake and related data tooling, sufficient to communicate effectively with technical teams.
  • Problem-solving mindset: Intellectual curiosity, strong investigative skills, attention to discrepancies, and a continuous desire to learn and improve.
  • Leadership style: Empathetic, adaptable, collaborative, and comfortable giving and receiving constructive feedback while remaining focused on outcomes.
  • Preferred background: Experience in insurance, financial services, or another regulated industry; contact center or operations experience; familiarity with Amazon Connect; Snowflake-based analytics; or hands-on experience defining dashboards and data products used by operational teams.

  Benefits

  • Competitive compensation: Base salary ranging from approximately $130,000 to $160,000 annually depending on geographic market, plus eligibility for a bonus.
  • Comprehensive healthcare: Medical, dental, and vision insurance options for eligible employees and their families.
  • Insurance protection: Basic and supplemental life insurance, as well as short- and long-term disability coverage.
  • Retirement benefits: Access to a 401(k) plan with employer matching contributions.
  • Wellness support: Employee Assistance Program and wellness programs available to all employees, regardless of hours worked.
  • Remote flexibility: Fully remote position within the United States.
  • Impactful work: Opportunity to influence operational strategy, analytics adoption, AI initiatives, and measurable business outcomes.
  • Collaborative environment: Work across operations, data, engineering, and leadership teams in a culture that values collaboration, communication, inclusion, and continuous improvement.
  • Growth opportunities: Exposure to modern analytics, AI, data products, and strategic operational transformation.