Remote Peak Sales Forecasting Expert - AI Trainer ($200-$275 per hour)
Remote Peak Sales Forecasting Expert - AI Trainer ($200-$275 per hour)
Mercor • Hemet, California, 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
or
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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