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- Tasks: Predict future drug performance using data analysis and modelling.
- Company: ZS is a leading management consulting firm dedicated to improving lives globally.
- Benefits: Enjoy flexible working, health benefits, and professional development opportunities.
- Why this job: Join a diverse team making a real impact in healthcare with innovative solutions.
- Qualifications: 4+ years in pharmaceutical forecasting and strong analytical skills required.
- Other info: Travel for client-facing roles offers unique experiences and insights.
The predicted salary is between 43200 - 72000 £ per year.
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Pharmaceutical Forecasting Consultant, London
Client: ZS
Location: London, United Kingdom
Job Category: Other
EU work permit required: Yes
Job Reference: 6b1d2296f95d
Job Views: 4
Posted: 12.08.2025
Expiry Date: 26.09.2025
Job Description:
ZS is a management consulting and technology firm focused on improving life. Our most valuable asset is our people. Here you’ll work with experts shaping life-changing solutions for patients, caregivers, and consumers worldwide. We value diversity, equity, and inclusion, supporting our employees to thrive.
Pharmaceutical Forecasting Consultant
Within our Forecasting division, the goal is to predict future drug performance, such as sales, demand, market share, or patient adoption, using data analysis, modeling, and business insights.
What You’ll Do
- Gather historical sales data for drugs.
- Collect epidemiological data (disease prevalence, incidence rates).
- Obtain market intelligence: competitor products, pricing, market share.
- Clean and structure data for analysis (handle missing values, outliers, inconsistencies).
- Analyze patient populations (target size, treatment patterns).
- Assess disease burden and trends.
- Study market dynamics, such as competitor launches, generics, patent expirations.
- Evaluate physician prescribing behaviors and treatment guidelines.
- Use statistical methods (time series, regression) to predict sales.
- Apply advanced techniques like machine learning for demand prediction.
- Perform scenario modeling under different market conditions.
- Incorporate seasonality, market growth, and promotional activities.
- Test assumptions under various scenarios (price changes, regulatory changes).
- Identify key drivers of forecast outcomes.
- Conduct sensitivity analysis on input changes.
What You’ll Bring
- 4+ years of forecasting experience in the pharmaceutical/life sciences industry.
- Strong analytical skills, including use of R, SAS, Tableau, or VBA.
- Experience with EU/UK projects.
- STEM-related degree.
We offer comprehensive benefits including health, financial planning, professional development, and flexible working arrangements. Travel is required for client-facing roles, providing opportunities to gain diverse experiences.
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Pharmaceutical Forecasting Consultant employer: ZS
Contact Detail:
ZS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Pharmaceutical Forecasting Consultant
✨Tip Number 1
Network with professionals in the pharmaceutical and life sciences sectors. Attend industry conferences, webinars, or local meetups to connect with people who can provide insights into the role and potentially refer you to opportunities at ZS.
✨Tip Number 2
Familiarise yourself with the latest trends in pharmaceutical forecasting and data analysis techniques. Being knowledgeable about current methodologies, such as machine learning applications in demand prediction, will set you apart during discussions.
✨Tip Number 3
Prepare for potential interviews by practising your analytical skills using real-world data sets. This could involve creating forecasts based on historical sales data or simulating market scenarios to demonstrate your problem-solving abilities.
✨Tip Number 4
Showcase your experience with relevant software tools like R, SAS, or Tableau in conversations. Be ready to discuss specific projects where you've successfully applied these tools to drive insights and make data-driven decisions.
We think you need these skills to ace Pharmaceutical Forecasting Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in pharmaceutical forecasting. Emphasise your analytical skills and any specific tools you've used, such as R, SAS, or Tableau.
Craft a Compelling Cover Letter: Write a cover letter that connects your background to the job description. Discuss your experience with data analysis and forecasting, and how it aligns with ZS's goals in improving life through data-driven insights.
Showcase Relevant Projects: If you have worked on projects related to drug performance prediction or market analysis, include these in your application. Detail your role and the impact of your work to demonstrate your expertise.
Highlight Soft Skills: In addition to technical skills, mention your ability to work in diverse teams and communicate complex data insights effectively. ZS values diversity and collaboration, so showcasing these traits can strengthen your application.
How to prepare for a job interview at ZS
✨Showcase Your Analytical Skills
As a Pharmaceutical Forecasting Consultant, strong analytical skills are crucial. Be prepared to discuss specific examples of how you've used tools like R, SAS, or Tableau in your previous roles. Highlight any projects where your analysis directly influenced business decisions.
✨Understand Market Dynamics
Familiarise yourself with current trends in the pharmaceutical industry, including competitor products and market share. During the interview, demonstrate your knowledge of how these factors can impact forecasting and be ready to discuss how you would approach scenario modelling.
✨Prepare for Technical Questions
Expect technical questions related to statistical methods and data analysis techniques. Brush up on time series analysis, regression models, and machine learning applications in forecasting. Being able to explain these concepts clearly will show your expertise.
✨Emphasise Team Collaboration
ZS values diversity and teamwork, so be sure to highlight your experience working in collaborative environments. Share examples of how you've successfully worked with cross-functional teams to gather data and insights, and how this has contributed to successful forecasting outcomes.
