Wholesale Analytics Intern at Arc'teryx in Portland, OR
- Company: Arc'teryx
- Location: Portland, Oregon
- Job type: full time
- Workplace: hybrid
- Posted: 2026-09-22
Job description
Department: NAM - Wholesale Reports to: National Account Manager - USA Location: Portland, Oregon Work Arrangement: Flexible, between in-office and home Pay Range: $21.49 - $26.49/hourly; pay is dependent on year of study and related experience Duration: Eight (8) months, January 4, 2027 – August 13, 2027 Hours Per Week: Full-Time (40 hours per week, Monday to Friday) Your Co-Op Opportunity at ARC’TERYX: As the Wholesale Analytics Intern, you support the US Wholesale Key Accounts team in turning sales, inventory, and account data into timely actions that improve in-season performance. You monitor sell-through and available-to-sell (ATS) inventory, connect the two data sets, and identify products, sizes, colors, or accounts where incremental orders may be possible. You help manage the weekly ATS order process from opportunity identification through follow-up, while maintainingaccurate reports, forms, and shared data. You will use Power BI, SPS Commerce, Excel, and internal systems, and learn how sales, planning, operations, and wholesale partners work together. You are encouraged to question inefficient processes, improve how the team organizes information, and communicate recommendations clearly. This role is ideally based out of Portland, Oregon, and is eligible for a hybrid work schedule. Meet Your Future Team: The US Wholesale Key Accounts team is accountable for delivering sales through all local channels. We meet the guest where they are shopping, and ensure Arc’teryx is represented in an authentic, consistent way. As the retail landscape changes, we will work together to evolve our approach with creativity and teamwork. If you were Wholesale Analytics Intern now, here are some of the core activities you would be doing: Analyzing sales and inventory performance to identify trends, risks, and opportunities across wholesale accounts Supporting in-season sales opportunities by reviewing ATS inventory, recommending additional orders, and assisting with the weekly order process Creating and maintaining business reporting using tools such as Excel, Power BI, and SPS Commerce to help the Sales team make informed decisions Improving team processes and data organization by supporting account documentation, maintaining accurate information, and identifying more efficient ways of working Here are some of the things you will learn by the end of your Co-Op placement: You will learn how to interpret retail sell-through, inventory, and order data within a wholesale commercial environment, and how to translate analysis into an actionable sales recommendation. You will strengthen your skills in Power BI, Excel, SPS Commerce, data quality, process documentation, and business communication. You will also gain exposure to cross-functional decision making, account management, demand and inventory considerations, and the full path from insight to order execution. Are you our next Wholesale Analytics Intern? You are currently enrolled in a post-secondary institution, preferably in Business, Statistics, Data Analytics, Finance, Economics, Supply Chain, Information Systems, or a related discipline You are comfortable working with numbers and spreadsheets and are interested in finding the business story behind the data You have advanced Microsoft Excel skills, including organizing data, using formulas, and reviewing large data sets. Experience with pivot tables or lookups is a requirement You are curious about Power BI and data visualization. Previous experience is helpful but not required if you are eager to learn You bring strong attention to detail and understand that accurate product, inventory, and order data is essential to good decisions You can manage recurring weekly responsibilities while progressing longer-term projects and meeting deadlines You communicate clearly in writing and conversation and are willing to ask questions when information is incomplete or unclear You can work independently once trained, while collaborating effectivel
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