Senior Forecasting & Planning Analyst

Job summary

The analyst will own demand forecasting for the Enterprise/B2B channel and develop strategic planning methodologies across all business segments. They will also build automated data tools and partner cross-functionally to improve forecast accuracy and inventory efficiency.

Job details

About the Role We're growing our Forecasting & Planning team to support the business's increasingly complex channel mix — most notably our rapidly scaling Enterprise/B2B business. This role sits upstream of tactical execution, focused on strategic demand planning, cross-functional partnership, and channel-specific ownership. You'll partner closely with the Senior Manager and a Forecasting Analyst to build the planning function's next chapter. This role is salaried with a compensation range of $85,000-$95,000 based on the candidate's experience, skills, competencies, qualifications and market. What You'll Own Enterprise/B2B channel planning: Serve as the primary forecasting and planning owner for the Enterprise channel, partnering directly with Sales and Account Management to translate pipeline and account-level signals into demand forecasts Strategic demand planning: Own the higher-level forecasting methodology and assumptions feeding the overall revenue forecast (DTC, Enterprise, Amazon, Wholesale), stepping back from day-to-day tactical placement to focus on scenario planning, risk-flagging, and forecast accuracy improvement Tooling & automation: Build and maintain BigQuery-based data pulls, automate recurring reporting/forecasting workflows, and apply AI tools to speed up analysis — reducing manual, spreadsheet-dependent processes over time S&OP-style cross-functional partnership: Represent planning in cross-functional forecast reviews with Sales, Finance, and Product; translate business context into planning assumptions and vice versa New product introduction (NPI) planning: Partner with Product Development on demand forecasting for new launches, building forecast logic for products with no historical sell-through Product lifecycle strategy: Own the strategic view of lifecycle management — discontinuation timing, overstock/understock risk, and recommendations tied to broader merchandising strategy (with room to grow into deeper merch collaboration as the team scales) Process & methodology improvement: Identify and implement improvements to forecasting models, planning cadences, and tools as the team's complexity grows Strategic analysis: Contribute ad hoc analysis supporting business-wide decisions (assortment, channel investment, inventory strategy) What Success Looks Like Shared accountability with the team on: MAPE: ≤10% across all channels (with specific ownership of Enterprise channel accuracy) In-Stock Rate: 95% combined / 98% on Enterprise All-Star SKUs / 98% on Top 5 SKUs DIO: contributing to inventory efficiency through better upstream forecast quality Average Parcel Zone: supporting network/inventory placement decisions that improve transit speed and cost What You Bring 5–7 years of experience in demand planning, merchandising planning, or forecasting, ideally with prior experience in a formal planner-type role Experience with B2B/non-DTC planning is a strong asset (account-based, pipeline-driven, or lumpy-demand forecasting) Comfort operating strategically and upstream — someone who can build a point of view on "what should the forecast assume" rather than just executing against a set plan Strong cross-functional communication skills; comfortable presenting forecasts and recommendations to non-planning stakeholders Bonus: experience with NPI forecasting or product lifecycle management Technical Skills (high priority) This role requires someone who can build and own tools, not just operate within them: BI tools: Advanced proficiency in Power BI, Tableau, or Looker — building dashboards and reports from scratch, not just consuming them SQL / BigQuery: Comfortable writing and optimizing queries to pull and model data directly from the warehouse, reducing dependency on other teams for data access Automation: Track record of automating manual, repetitive planning processes (e.g., scripting recurring reports, automating data refreshes, building repeatable forecast pipelines) rather than rebuilding spreadsheets each cycle AI/LLM tools: Hands-on experience applying AI tools (e.g., Claude, ChatGPT, Copilot, or similar) to accelerate analysis, generate code/scripts, summarize data, or build forecasting logic Advanced Excel: Experience with complex modeling, but not the primary tool for scaled work Python or similar scripting experience is a strong asset, particularly for automation or forecast modeling

What you’ll do

The analyst will own demand forecasting for the Enterprise/B2B channel and develop strategic planning methodologies across all business segments. They will also build automated data tools and partner cross-functionally to improve forecast accuracy and inventory efficiency.

Requirements

Candidates must have 5–7 years of experience in demand planning or forecasting with strong technical proficiency in SQL, BI tools, and automation. The role requires a strategic mindset capable of building forecasting models and effectively communicating insights to non-planning stakeholders.

Listed skills

• Forecasting · Preferred
• SQL · Preferred
• Power BI · Preferred
• Tableau · Preferred
• Python · Preferred
• Scenario Planning · Preferred
• Cross-Functional Collaboration · Preferred
• Inventory management · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Demand planning
• Forecasting
• SQL
• BigQuery
• Power BI
• Tableau
• Looker
• Automation
• Data modeling
• Python
• Scenario planning
• Cross-functional collaboration
• Inventory management
• Product lifecycle management
• AI tools
• Advanced Excel
• Strategic Analysis
• Ad Hoc Analysis
• Sales and Operations Planning
• ChatGPT
• Pipelines
• Accountability
• Revenue Forecasting
• Workflow Management
• Demand Planning
• Planning
• Data Access
• Account Management
• Artificial Intelligence
• Business To Business
• Business Intelligence
• Google BigQuery
• Dashboard
• Spreadsheets
• Communication
• Data Modeling
• Demand Forecasting
• Finance
• Sales
• Warehousing
• Python (Programming Language)
• Product Lifecycle Management
• Merchandising
• New Product Development
• Query Optimization
• Scenario Planning
• Stock Keeping Unit
• SQL (Programming Language)
• Tableau (Business Intelligence Software)
• Tooling

Job areas

• Data & Analytics
• Finance & Accounting
• Management & Leadership
• Technology
• Retail
• Forecasting and Planning Manager
• Demand Planning Analyst
• Industrial and Production Engineers
• Logistics Analysts
• Logisticians

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