Health Economic Modelling - Senior Consultant/Engagement Manager - Multiple locations at IQVIA

Barcelona, Catalonia, Spain

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Pharmaceutical, HealthcareIndustries

Requirements

Advanced degree (PhD, MSc, or equivalent) in Health Economics, Public Health, Epidemiology, or a related scientific field
Minimum of 5 years of experience in health economics
Experience with ex-novo HEOR models building
Experience in the pharmaceutical or healthcare consulting industry working for HQ
Proven experience in project management, including planning, execution, and delivery of complex projects
Strong analytical skills and proficiency in health economic modelling software (e.g., TreeAge, Excel, R)
Excellent communication and presentation skills, with the ability to convey complex information to diverse audiences
Ability to work independently and as part of a team in a fast-paced, dynamic environment
Strong organizational skills and attention to detail
Preferred Qualifications
Publications in peer-reviewed journals related to health economics, diabetes, or obesity
Knowledge of global health systems and reimbursement processes
Preference for experience in modelling chronic diseases

Responsibilities

Lead and manage health economics projects focused on diabetes and obesity, ensuring timely delivery and high-quality outcomes
Serve as the primary point of contact for clients, providing expert advice and guidance on health economics models and methodologies
Develop and implement health economic models to support the value proposition of diabetes and obesity treatments
Conduct literature reviews, data analysis, and interpretation to inform model development and validation
Present findings and recommendations to clients, stakeholders, and internal teams through reports, presentations, and publications
Contribute to the dissemination of research findings by drafting scientific manuscripts, reports, and presentations for publication in peer-reviewed journals and conferences
Stay current with the latest research, trends, and best practices in health economics with a focus on diabetes and obesity

Skills

Health Economic Modelling

Diabetes Modelling

Obesity Modelling

Markov Models

Patient-Level Modelling

HTA

Real-World Evidence

Advanced Analytics

Literature Reviews

Value & Access

IQVIA

Advanced analytics and clinical research services

About IQVIA

IQVIA provides advanced analytics, technology solutions, and clinical research services specifically for the life sciences industry. Their services utilize extensive data resources and technology to create connections within healthcare, allowing clients to gain insights that help speed up the development and marketing of new medical treatments. This process is facilitated by their IQVIA Connected Intelligence™ system, which offers quick and flexible insights. IQVIA stands out from competitors by focusing on patient privacy, employing various technologies to protect individual data. The company's goal is to enhance healthcare outcomes by supporting biotech, pharmaceutical, and medical device companies, as well as researchers and government agencies, in understanding diseases and advancing medical science.

Durham, North CarolinaHeadquarters

1998Year Founded

$3,526MTotal Funding

POST_IPO_EQUITYCompany Stage

Cybersecurity, Biotechnology, HealthcareIndustries

10,001+Employees

Risks

Rapid advancement of cancer vaccines may disrupt traditional clinical research models.

Proliferation of disparate technological solutions causes technology overload in clinical trials.

Generative AI technologies face challenges in adoption due to data privacy concerns.

Differentiation

IQVIA leverages advanced analytics and big data for life sciences solutions.

The company offers privacy-enhancing technologies to protect individual patient data.

IQVIA's AI Assistant provides rapid, actionable insights for healthcare and life sciences.

Upsides

Increased adoption of decentralized clinical trials enhances patient-centric study designs.

AI-driven drug discovery accelerates identification of potential drug candidates.

Expansion of telemedicine facilitates remote patient monitoring and data collection.

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