Senior Business Analyst

MOJOAlcoa, TN

About The Position

As a MOJO Senior Business Analyst, you are the bridge between data and action, the strategist who transforms real-time performance signals into clear, operational decisions. You partner closely with Operations, Leadership, and Executive teams to bring visibility, structure, and accountability to how the business performs at every level. You don’t just report what happened; you explain why it happened, what’s likely to happen next, and what leaders should do about it. You design systems that allow teams to manage by exception, focus on what matters most, and move faster with confidence. At MOJO, this role sits at the intersection of analytics, technology, and operations. You will own the analytics lifecycle end-to-end: defining KPIs, building dashboards, testing hypotheses, developing projections and pro formas, and integrating AI-enabled tools that continuously improve how the business sees itself and performs. If you thrive in a fast-paced, operationally driven environment and love turning complexity into clarity, this role is for you.

Requirements

  • 5+ years of experience in business analytics, systems analysis, or data-driven operational roles
  • High proficiency in database management and data modeling
  • Strong experience developing dashboards, performance reports, and process documentation
  • Demonstrated ability to translate complex data into clear, actionable insights
  • Exceptional written and verbal communication skills

Nice To Haves

  • Bachelor’s degree (or equivalent experience) in Information Technology, Computer Science, Data Analytics, or a related field
  • Advanced working knowledge of Microsoft applications and Smartsheet
  • Proven experience managing projects, system implementations, and user testing
  • Extensive experience with data visualization and executive-level reporting tools
  • High proficiency in technical and business documentation
  • Experience integrating AI or advanced automation into analytics and reporting environments

Responsibilities

  • Design, implement, and maintain KPI frameworks that provide real-time and exception-based visibility into sales, operations, and financial performance.
  • Identify patterns, trends, and performance gaps through advanced analytics and continuous system evaluation.
  • Build standardized dashboards and reporting systems that are trusted and used across the organization.
  • Enable leaders to manage by exception through alerts, thresholds, and predictive insights.
  • Design and deliver ad hoc analytical reports that provide real-time visibility into site, regional, and enterprise performance.
  • Analyze labor and workforce data to identify trends, inefficiencies, and opportunities, and translate findings into clear, actionable recommendations for Operations and Leadership.
  • Evaluate site-level performance drivers—including location dynamics, membership volume, traffic patterns, and market conditions—to determine the most relevant KPIs and success metrics for each site.
  • Evaluate, analyze, and communicate business and system requirements on an ongoing basis.
  • Develop clear, structured documentation for analytics processes, reporting standards, and system workflows.
  • Partner with internal and external stakeholders to ensure optimized system integration and reliable data flow.
  • Lead and support system implementations, user testing, and continuous improvement initiatives.
  • Serve as a thought partner to Operations, Leadership, and Executive teams.
  • Respond to leadership questions with research-backed insights, recommendations, and scenario analysis.
  • Lead hypothesis testing, projections, pro formas, and forecasting to support operational and financial planning.
  • Translate complex technical findings into clear, actionable business narratives.
  • Partner with technical teams to integrate AI-driven tools and automation into analytics and reporting workflows.
  • Identify opportunities to streamline reporting, improve data accuracy, and accelerate insight delivery.
  • Continuously evolve analytics systems to support smarter, faster, and more proactive decision-making.
  • Leverage AI-enabled analytics and decision-support tools to enhance forecasting, pattern recognition, and data-driven insight generation across operational and labor models.
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