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Bevi
Supply Chain Data AnalystBevi • Boston, MA, United States
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Supply Chain Data Analyst

Supply Chain Data Analyst

Bevi • Boston, MA, United States
12 days ago
Job type
  • Full-time
Job description

Supply Chain Data Analyst

Bevi is on a mission to transform how beverages are delivered and consumed. Our connected beverage platform eliminates the need for single-use bottles and cans, making it easy, fun, and sustainable to stay hydrated. As the category leader in IoT-enabled beverage technology, we're building a future where Bevi machines are everywhere people live, work, and connect. We've raised over $160M in venture capital, serve thousands of customers across the US, Canada, UK and Ireland, and we've been rapidly growing year over year, saving over 1 billion bottles from waste. In addition to driving hypergrowth with our current product line, Bevi is heavily investing in new product development.

The Supply Chain Data Analyst will play a critical role in evolving Bevi's operational efficiency by managing the tactical procurement of components while simultaneously auditing and modernizing our core supply chain workflows. This role serves as a hybrid practitioner and internal consultant, bridging the gap between current manual purchasing processes and a future state powered by automation, seamless system integration, and AI. Operating with a blend of extreme detail orientation and technical aptitude, you will partner with Global Supply Managers (GSMs) and cross-functional teams to ensure data integrity, identify bottlenecks, and propose scalable solutions. This is a high-impact opportunity to influence how a high-growth hardware startup leverages emerging technology to scale its supply chain and master data operations.

Key Responsibilities

  • Tactical PO Execution: Partner with the Planning and Global Supply Management (GSM) team to execute day-to-day purchasing, managing PO issuance, tracking delivery schedules, and handling routine expedites to align with production needs.
  • Invoice & Receiving Resolution: Act as the first line of defense for tactical discrepancies, investigating and correcting data when vendor shipments or invoices do not match ERP records.
  • Master Data Governance: Take ownership of SKU and BOM accuracy, acting as the gatekeeper for our "single source of truth" across core platforms (e.g., NetSuite, Arena).
  • Process Mapping & Documentation: Lead the discovery of "current state" procurement workflows, identifying manual handoffs and creating visual maps or SOPs to standardize supply chain operations.
  • Automation Opportunity Assessment: Analyze documented purchasing and inventory processes to identify repetitive tasks ripe for automation using tools like Zapier, Workato, or native ERP functionalities.
  • AI Implementation Research: Investigate and pilot AI-driven use cases (such as LLM assisted data cleaning, automated vendor follow-ups, or predictive stock alerting) to reduce administrative overhead.
  • Continuous Improvement Reporting: Build simple dashboards to track supply chain KPIs (e.g., PO cycle time, on-time delivery) and the "before and after" impact of implemented process changes.

Qualifications

  • Bachelor's or Master's degree in Supply Chain Management, Business Analytics, Industrial Engineering, Information Systems, or 1-3 years of equivalent practical experience.
  • Strong analytical mindset with an obsession for detail and a knack for "connecting the dots" between master data, procurement execution, and downstream business functions.
  • Proficiency in ERP systems (NetSuite preferred) and PLM software (Arena), alongside advanced Excel/Google Sheets skills (Pivot Tables, VLOOKUPs/XLOOKUPs). Exposure to or high interest in automation platforms, process mapping tools (e.g., Lucidchart, Miro), and AI tools (ChatGPT/Claude for work, API basics, or low-code environments).
  • Excellent communication skills, with the ability to translate "supply chain pain" into clear technical requirements for engineering and finance stakeholders.
  • A self-starter attitude with the instinct to fix the root cause of data errors or slow processes, rather than just treating the symptoms in a fast-paced, high-growth environment.

What Success Looks Like

  • Operational Stability: Consistent, accurate execution of all buyer responsibilities with a visible reduction in "fire drills" caused by data silos or manual handoffs.
  • Improved Data Integrity: Maintenance of a highly accurate "single source of truth" within our primary systems (NetSuite/Arena) that perfectly mirrors GSM-negotiated terms.
  • Comprehensive Process Library: Delivery of a centralized repository of documented core procurement and master data workflows that are easy for the team to navigate and update.
  • Measurable Efficiency Gains: Successful implementation of at least 2-3 automation or AI assisted "quick wins" that reduce manual data entry or administrative work hours for the supply chain team.
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Supply Chain Data Analyst • Boston, MA, United States

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