[Hiring] Senior Forecasting & Planning Analyst @Branch

Role Description

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

• 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.

Qualifications

• 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.

Requirements

• 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: A strong asset, particularly for automation or forecast modeling.