Operations Analytics Lead in New York at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Operations Analytics Lead based in United States.

This role sits at the intersection of operations, analytics, data, and emerging AI capabilities, with a strong focus on turning insights into measurable business outcomes.
You’ll own the portfolio of operational problems where data and analytics can create the greatest value, helping leadership prioritize what matters most.
Rather than simply producing reports, you’ll translate complex data into clear recommendations that influence decisions and improve real-world workflows.
You’ll partner closely with a central data and engineering organization, defining requirements and ensuring solutions are successfully delivered and adopted.
The role also provides an opportunity to shape how AI and agentic technologies are responsibly applied to operational challenges.
Success will be measured by improved decisions, adoption, and operational value—not simply by the volume of analytics delivered.
This is a fully remote, strategic role suited to an experienced analytics leader who combines strong judgment, influence, and operational fluency.

• 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.

• 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.

• 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.