Supply Chain Analytics & Anaplan Associate

Lime

12d•$94,000 - $104,000•Remote

About The Position

As the largest global shared micromobility business, Lime is on a mission to build a future where transportation is shared, affordable and carbon-free. A Time Magazine 100 Most Influential Company, Lime has powered more than one billion rides in close to 30 countries across five continents, spurring a new generation of clean alternatives to car ownership. Learn more at li.me. Lime is hiring a Supply Chain Analytics & Anaplan Associate to join our Supply Chain Planning & Logistics team! Reporting to the Senior Manager, Demand Planning & Analytics, you’ll improve the quality, visibility, and usability of data across demand planning, supply planning, and logistics. The role combines reporting and data analysis with hands-on support for Lime’s supply chain Anaplan models. Working with business and technical partners, this role translates defined business needs into reliable reporting solutions, investigates data issues, supports Anaplan data integration, and serves as a day-to-day resource for model break-fixes and enhancements. The role works independently on recurring and defined assignments, while partnering with more experienced stakeholders on new or complex projects. The role uses approved AI and analytics tools to efficiently process, interpret, and validate supply chain data; identify trends and anomalies; accelerate root-cause analysis; and improve the usability of planning and reporting outputs. This is a remote position with a requirement for candidates to reside in the United States to maintain effective collaboration across teams.

Requirements

Bachelor’s degree in Supply Chain, Operations, Analytics, Engineering, Business, or a related field, combined with 2–4+ years in supply chain analytics, BI, planning support, or data management.
Hands-on experience with Anaplan (model support, testing, troubleshooting) and building/maintaining dashboards in Tableau or a similar BI platform.
Experience with NetSuite or another ERP system, including an understanding of how transactional and master data support planning and reporting.
Strong analytical skills and attention to detail, with a demonstrated ability to investigate data discrepancies and recommend practical solutions.
Demonstrated experience using generative AI, machine-assisted analytics, or automation tools to process, analyze, explain, or document data. Ability to validate AI-generated outputs, recognize limitations or inaccuracies, protect sensitive information, and apply sound business judgment.
Proven capability to gather requirements, define scope, and translate business/stakeholder needs into usable reporting and analytics outputs.
Effective cross-functional communication skills across planning, logistics, finance, and technical teams, with the ability to work independently and adjust methods as needed.

Nice To Haves

Anaplan Model Builder certification.
Proficiency with SQL, data integration concepts, data modeling, automated data-quality checks, and advanced spreadsheet reconciliation.
Functional knowledge of demand/supply/inventory planning, logistics, or S&OP processes, ideally in a multi-market or global supply chain environment.
Familiarity with data governance, lineage, rep

Responsibilities

Build & Maintain Visualizations: Develop and maintain Tableau dashboards across demand, supply planning, and logistics, partnering with process owners to align requirements with business goals.
Ensure Data Quality & Governance: Investigate data discrepancies to resolve root causes, while tracking reporting adoption, usage, and quality feedback across teams.
Manage Anaplan Integrations: Support Anaplan data pipelines (inputs, outputs, downstream feeds) and proactively identify data gaps that impact planning accuracy.
Validate & Document Data Flows: Partner with stakeholders to test and reconcile Anaplan reporting outputs while documenting business logic, data sources, and validation steps.
Triage Model Issues: Serve as the primary day-to-day resource for resolving supply chain model break-fix issues. Escalate issues involving model architecture, material planning-policy changes, or significant cross-functional tradeoffs to the model owner or appropriate senior stakeholder.
Drive Model Enhancements: Coordinate model updates from requirements gathering and testing to deployment, while continuously improving repeatable validation processes.
Manage Intake & Prioritization: Maintain the intake pipeline for supply chain planning and logistics analytics requests, scoping opportunities based on impact, effort, and timing.
Apply AI-Enabled Analytics: Use approved generative AI and analytical tools to summarize large datasets, identify anomalies and trends, support exploratory analysis, and develop hypotheses for supply chain issues. Validate AI-generated insights against source data and business context before sharing recommendations.