Remote Peak Sales Forecasting Expert - AI Trainer ($200-$275 per hour)Mercor • Chesapeake, Virginia, US
Remote Peak Sales Forecasting Expert - AI Trainer ($200-$275 per hour)
Mercor • Chesapeake, Virginia, US
[job_card.variable_days_ago]
[job_preview.job_type]
- [job_card.part_time]
- [filters.remote]
[job_card.job_description]“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.
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
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Sales Expert • Chesapeake, Virginia, US
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