Director of US Forecasting

Taylor-Strategy-Partners; Princeton (NJ); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Taylor Strategy Partners invites applications for the Director of US Forecasting. This role leads hands-on US commercial forecasting efforts, develops short- and long-term forecast methodologies, and drives actionable business decisions in partnership with US Commercial and Global leadership.

The role reports to the Sr. Director of Analytics and Commercial Operations and is based in Princeton, NJ in a hybrid model, closely aligned with US business leadership.

Qualifications

• 8–12 years of experience in revenue forecasting, pharma preferred.
• Hands-on ownership of in-line product forecasts and performance explanations.
• Experience applying multiple forecasting methodologies to support planning.
• Strong cross-functional collaboration and communication skills.
• Knowledge of pharmaceutical data sources and reporting.
• Experience presenting to senior leadership.

Responsibilities

• Lead development of in-line US patient and revenue forecasts for the therapeutic area.
• Apply fit-for-purpose forecasting methods for short-term and long-term planning.
• Integrate data sources with US Analytics & Commercial Operations.
• Monitor forecast accuracy and explain variances to leadership.
• Translate research and competitive insights into forecast assumptions.
• Present forecast results, risks, and recommendations to senior leadership.
• Support brand planning, contracting, and field execution with data-driven insights.
• Continuously improve forecasting methodologies and processes.

Skills

Revenue forecasting

Inline pharmaceutical forecasting

ARIMA / Holt-Winters

Scenario planning

Executive communications

Education

Bachelor's degree

Master's or MBA preferred

Tools

Forecasting software

Job description

Description

The Director of US Forecasting will be responsible for leading hands-on, in-line US commercial forecasting efforts, performance reporting, and the development of short- and long-term forecast methodologies to drive impactful decision-making.

This highly visible role will serve as a trusted partner to US Commercial and Global leadership, translating forecast outputs, assumptions, and performance drivers into clear business implications and actionable decisions.

The Director will report to Sr. Director of Analytics and Commercial Operations and be based in Princeton, NJ in a hybrid model and will be heavily integrated with US business leadership.

Responsibilities

• Lead the development and evolution of in-line US patient and revenue forecasts in the therapeutic area, applying fit-for-purpose methodologies for short-term operational forecasting and long-term strategic planning.
• Select, build, and refine forecasting approaches for in-line products, including patient flow, causal, patient dynamics, trend-based/statistical methods, and scenario modeling, to support both near-term performance management and long-range business planning.
• Partner with the broader US Analytics & Commercial Operations team and USBU business partners to integrate data sources, pressure-test assumptions, quantify risks and opportunities, and update in-line product forecasts as market conditions evolve.
• Monitor in-line product forecasts against actual performance, explain variances, and continuously improve methodologies, assumptions, and forecast accuracy over time.
• Leverage national and sub-national analytics to understand demand drivers and patient journey dynamics, identifying how changes in diagnosis, prescribing, access, fulfillment, persistence, and adherence affect in-line product performance and forecast accuracy.
• Partner closely with Marketing, Market Access, Patient Services, Sales Leadership, and Incentive Compensation teams to translate analytics into actionable recommendations that support brand planning, contracting strategies, field force effectiveness, resource allocation, and broader commercial decision-making.
• Present in-line product forecast results, assumptions, risks, and opportunities to senior leadership, providing recommendations that drive business decisions.
• Support in-line brands through data-driven decision-making, including scenario modeling, forecast assessments, competitive assessments, and evaluation of short- and long-term business drivers.
• Continuously review and improve in-line forecasting methodologies and processes, applying industry best practices to enhance forecasting capabilities.
• Commission primary and secondary research to inform competitive intelligence, evaluate the potential impact of new market entrants, and incorporate insights into forecast assumptions.
• Lead demand studies and other quantitative research to calibrate forecast assumptions, validate key inputs, and complement national and sub-national analytics.
• Monitor competitor communications, investor calls, clinical and regulatory updates, and other external signals to assess competitive landscape changes and potential forecast implications.
• Translate primary and secondary research, and competitive intelligence findings into clear insights, forecast implications, and recommendations for senior leadership and cross-functional business partners.

Requirements

• The ideal candidate will be a highly analytical and strategic thinker with 8-12 years of experience and a proven track record in revenue forecasting, ideally within the pharmaceutical or healthcare industry.
• Education: Bachelor's degree required; Master's degree (MS, MBA) in a quantitative or healthcare-related discipline strongly preferred.
• Required: Direct, hands-on experience owning in-line pharmaceutical product forecasts, including accurate short- and long-range patient-based and revenue models; monitoring forecast performance; explaining variances; and continuously improving forecast accuracy over time.
• Required: Demonstrated experience applying forecasting methodologies - including patient flow, causal modeling, patient dynamics, trend-based forecasting, Holt-Winters, ARIMA, and single or multiple linear regression to actively marketed, in-line pharmaceutical products.
• Knowledgeable in pharmaceutical data sources and potential deficiencies.
• Required: Experience applying multiple forecasting methodologies to in-line products to support short-term operational outlooks, long-range strategic forecasts, scenario planning, and ongoing performance management.
• Deep understanding of market dynamics, competitor activity, market access conditions, field execution, brand planning, contracting, and regulatory changes, with the ability to anticipate shifts and quantify their potential business impact.
• Strong communicator with experience presenting complex insights to senior leadership
• Proven ability to collaborate cross-functionally with teams
• Proactive, detail-oriented, and skilled in identifying risks and opportunities
• Continuous improvement mindset, focused on enhancing forecasting methodologies and processes
• Ability to build and maintain strong relationships with key stakeholders across the organization
• Adaptable to a fast-changing business environment
• Demonstrated ability to develop and communicate in-line product forecasts that influence strategic planning decisions across market access, field planning, brand planning, contracting, and monthly business reviews.
• Knowledge of industry best practices in forecasting, with a passion for leveraging new tools and technologies to improve efficiency
• Required: US pharmaceutical forecasting experience with direct accountability for established, commercially available in-line brands.
• Strong understanding of financial and operational aspects of forecasting

TSP Talent Solutions and our customers are affirmative action/equal opportunity employers (Minorities/Females/Veterans/Disabled)

#tsp-search

#LI-Remote

#tsp-search

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.