Sales & Operations Analytics Engineer

(also fielded as: Analytics Engineer, BI Engineer, Commercial Analytics Analyst)

turn is a family-founded, independent brand operating across CA, AZ, NY, and FL. We run lean and we build with intention. This role exists because our reporting has to get dialed in, and we need one technical builder who can own the truth of our numbers end to end.

Own a single source of truth for sales and operations. Pull the raw reports from our distributors and distribution partners, compile them with COGS, and turn them into decision-grade reporting: revenue, collections, inventory, supply chain, sell-through, and sales velocity, account by account, trending 12 months.

You are the engine behind our Sales and Operations Planning (S&OP) process. You build the truth and sit in the room. You do not own the forecast. That call sits with Sales, Ops, and leadership. Your job is to make sure leadership is deciding from clean numbers, not fighting about whose spreadsheet is right.

This is a build role, not a maintain role. You are standing up the foundation,
not inheriting a finished one.

Today we have a strong sell-in reporting layer in Tableau: wholesale revenue by AE, by account, by category, by retailer, by strain, for CA and NY. That is the floor.

• Extend the model to all four markets: CA, AZ, NY, FL. + D2C and new 2026/2027 markets
• Add the layer we do not have yet: sell-through and depletion. What the retailer actually sold off the shelf, not just what we shipped them. This is the hard part and the reason this role exists.
• Stand up inventory, supply chain, collections, and account-level P&L on the same foundation.

• Ingest distributor and distribution depletion, shipment, and inventory reports across multiple partners and multiple formats, via API wherever possible, automated wherever possible.
• Integrate sell-through from the platforms and partners that actually have it:
  Headset, Pistil Data, Sparkplug, and the retail chains that share their own POS (Catalyst and others).
• No one in cannabis has 100% sell-through. Assemble the best available coverage and label clearly what is true sell-through versus a sell-in proxy. Sell-in is internal and clean. Sell-through is external and partial, and stitching it together is the whole reason this role exists.
• Standardize the mess into one model: SKU mapping, account mapping, category and unit normalization across all four states.
• Build and own the data model everything else reads from. One source of truth, not a pile of spreadsheets.

• Inventory on hand, what is incoming, and what is in production.
• Revenue, and collections (AR aging), pulled on a reliable cadence from Finance.
• Sales history by SKU by month, account by account.
• Sell-through, sales velocity, and in-stock vs. out-of-stock at the account level.
• A weekly sales view: velocity and out-of-stock by account, with each rep able to pull their own book.
• Account-level P&L, quarterly to start, focused on revenue and net margin, with COGS tied in.
• 12-month trending across every metric above, at the same granularity the current scorecard runs: state, AE, account, retailer, category, strain.

• Run the monthly and quarterly sales commission calculations. Work with the reps to resolve every discrepancy, then hand a clean, final number to accounting for check and approval. Automate the calc so it stops being a monthly fire drill.
• PO vs. co-packer close-out. Expected quantity against actual, with over, under, waste, and damage broken out alongside supply chain.
• Sell-in vs. sell-through, so we can see where product is shipping but not moving.

• Build and ship the monthly S&OP pack: end-of-month capacity, what was planned to be brought in, what was actually brought in, what was actually sold, and what is carrying over.
• Sit in the planning conversations as the data owner. Pressure-test assumptions. Surface variance early enough to act on, not explain after the fact.

• Map every data source, owner, and format. Document where the data is dirty and why.
• Stand up the internal foundation…