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Operations Analyst (Entry-Level)
Operations Analyst (Entry-Level)KODE Labs • Detroit, MI, US
Operations Analyst (Entry-Level)

Operations Analyst (Entry-Level)

KODE Labs • Detroit, MI, US
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  • [job_card.full_time]
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Operations Analyst

KODE Labs is building the operating system for the built world. We're transforming how buildings operate, making them more intelligent, efficient, and sustainable at scale. Since 2017, we've partnered with some of the world's largest real estate portfolios to deliver measurable energy savings and operational excellence. But we're just getting started. The smart buildings industry needs bold thinking and better solutions. We're here to set the standard : moving fast, building fearlessly, and proving what's possible when technology meets infrastructure. At KODE, results speak louder than titles, and every person drives meaningful impact.

About The Role

As an Operations Analyst at KODE Labs, you will be the driving force behind leveraging business intelligence to maximize the productivity of the team. You will contribute to enabling strategic insights into the business that highlight bottlenecks in project delivery / revenue earn and provide tooling to help solve such issues. You will also be responsible for ensuring our revenue forecasting, operational insights, and core business systems are accurate, consistent, and decision-ready.

Your detailed responsibilities will include :

Revenue Ownership

  • Build and maintain a forward-looking revenue forecast that combines backlog, pipeline, and delivery progress
  • Identify revenue risk early by analyzing stalled work, delayed timelines, and execution drift
  • Conduct frequent revenue performance reviews that highlight key drivers, blockers, and required actions.

Operational Systems Ownership

  • Own the structure and reliability of operational tooling used to track delivery and revenue
  • Ensure systems are configured to support forecasting accuracy and operational visibility
  • Improve workflows and data structures to reduce manual effort and increase clarity in day-to-day work of the delivery team
  • Establish standards for tool usage and enforce data hygiene across teams
  • Cross-System Consistency & Integrity

  • Build, develop and maintain integrations between sales, delivery and accounting tools (ex. CRM ->
  • PM tooling)

  • Identify and reconcile mismatches across systems before they impact reporting
  • Build reconciliation routines that surface discrepancies proactively
  • Operational Insights & Efficiency

  • Analyze operational data to identify inefficiencies, bottlenecks, and recurring execution gaps
  • Structure leadership updates that clearly connect operational activity to revenue impact
  • Continuously improve reporting visibility so teams can act on real-time performance signals
  • Requirements

    1. Education in Business, Finance, Economics, Engineering, Computer Science, Data Science, or a similarly analytical field

    2. Strong analytical foundation with the ability to work through messy data and produce clear conclusions

    3. Understand and / or curiosity of basic business finance concepts, including revenue, margin, forecasting, and how companies track performance

    4. Proficiency in Microsoft Excel (modeling, structured analysis, pivots / lookups, building clean reporting tables)

    5. Strong written communication skills with the ability to summarize findings clearly for leadership

    6. High ownership, reliability, and ability to operate in a fast-paced environment with minimal hand-holding

    Preferred Qualifications

  • Strong interest in learning how revenue forecasting works in a real operating business and a desire to build that skill quickly
  • Curiosity and motivation to deeply understand how KODE's delivery engine operates and what data accurately captures delivery truth
  • Interest in working cross-functionally with Sales, Delivery, and Finance to connect the dots across the business
  • Ability to generate clear narratives of operational data into presentations that drive decisions
  • Comfort operating in ambiguity and willing to dig through incomplete or inconsistent data to establish clarity and structure
  • Measurements Of Success

  • Team leadership and other key stakeholders have access to predictable and reliable forecast numbers
  • Revenue bottlenecks and growth opportunities are identified and reported on proactively
  • Operational tools are user-friendly, and configured to maximize output with as little input
  • The team gets quantitatively faster due to not just identified pain points but also through pursued improvements
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