Peak Sales Forecasting Expert at Mercor

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. Key Skills Hr Executive Recruitment,Internship,AIX,Fleet,Information Technology Sales Employment Type : Full Time Experience: years Vacancy: 1