Remote Peak Sales Forecasting Expert - AI Trainer ($200-$275 per hour)Mercor • Waterbury, Connecticut, US

Remote Peak Sales Forecasting Expert - AI Trainer ($200-$275 per hour)

Mercor • Waterbury, Connecticut, US

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The client’s current peak-sales forecasting framework produces strong numerical outputs and narratives, but requires

real-world forecast accountability
— the kind held by people who’ve owned forecasts that drove BD, portfolio, or investment decisions.

We are looking for a senior commercial / forecasting expert to : - Write

“golden” peak-sales forecasts

for representative drug programs and standard prompts. - Define

structural checks, scenario logic, and sanity bands

for automated forecast evaluations. - Make explicit the

heuristics and base-rate assumptions

used by experienced forecasters to tell a realistic model from a speculative one. ###

Profile :

Industry Commercial Forecaster :

Director / Sr. Director / VP-level experience in

global forecasting, brand planning, or commercial insights

. - Built and defended

patient-based peak-sales models

used in portfolio, BD, or investment contexts. - Familiar with

forecasting for multiple drugs or indications

, particularly during pre-launch and early commercialization stages. - Can articulate the reasoning behind

base-case assumptions

(penetration, price, ramp, LOE) and how they evolve post-launch. - Has written or reviewed

governance-ready peak-sales models

(e.g., for launch committees or investor boards).

Market / VC / Buy-side Analyst :

Senior biotech equity analyst, VC incubation / BD lead, or company creation expert (e.g., from Third Rock, ARCH, Versant, RTW, Venrock, or similar). - Built patient-level and revenue models used for

investment diligence

asset valuation

. - Can critique or improve bottoms-up forecasts from an investor’s perspective, identifying optimistic biases and false comparables. ###

Experience level

~10–15 years in biotech / pharma forecasting, investment, or commercial strategy roles. - Experience spanning

pre-launch forecasts → post-launch actuals

for multiple assets. - CV / LinkedIn bullets like “led global forecast for \[drug\],” “responsible for long-range revenue planning and peak-sales scenarios,” or “built patient-based forecasts for portfolio decisions.” - Strong comfort with

market modeling logic

(TPP inputs → eligible pool → penetration → price / net → ramp + LOE). - Evidence of post-hoc learning — can articulate where real-world results diverged from base-case assumptions. ###

Expectations :

Inputs we give :

Forecast prompts (representative TPPs, analogs, and SoC / pricing / launch assumptions). - Access to anonymized or simulated data sets for building base cases.

Expected outputs (per prompt) :

Golden Forecast Output :

A benchmark-quality peak-sales forecast (peak value, revenue curve by key years) plus a concise narrative (3–5 key drivers, 2–3 downside risks). The output should show how the expert calibrates realistic vs. inflated scenarios. -

Forecast Rubric :

A structured evaluation framework with critical checks (market structure realism, patient flow logic, analog consistency, regional splits, LOE handling). Should define clear scoring thresholds — e.g., _unacceptable → excellent_. -

Know-how Layer :

Commentary explaining how experienced forecasters anchor their assumptions : - How they select base rates and analogs. - How they temper over-optimism (payer pushback, access limits, share ceilings). - How they identify when a model’s structure or magnitude is implausible. ###

Engagement Model & Compensation

Contract / Part-time (Remote)

— work flexibly with data science and evaluation teams.

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Sales Expert • Waterbury, Connecticut, US

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