Peak Sales Forecasting Expert

The clients current peak-sales forecasting framework produces strong numerical outputs and narratives but requires real-world forecast accountability the kind held by people whove 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 investors perspective identifying optimistic biases and false comparables.

Experience level

• 1015 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 (35 key drivers 23 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 models structure or magnitude is implausible.

Engagement Model & Compensation

• Contract / Part-time (Remote) work flexibly with data science and evaluation teams.