Study Optimization Manager

Key Skills

Aartificial intelligence, Effective communication skills, Financial Risk, Logistic Regression, Machine learning techniques, Optimization, Supply Chain Management, Transformer

Job Description

The Study Optimization Manager (SOM) role is accountable for the development, implementation and oversight of optimal clinical supply strategies using advanced modeling techniques and software for selected high-value clinical trials. This R&D enterprise responsibility impacts optimal design of clinical trials, acceleration of clinical supply, and oversight of strategic, enterprise-level risk mitigation and supply management.

This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:

• Develops demand and supply models for high-value clinical trials. Uses understanding of complex business problems, data formats, applicability of the data to the problem and standard and advanced modelling techniques, to create models that perform to specifications and cope with changes over time.
• Optimizes supply strategies initially and dynamically over the duration of the study to mitigate risk, maximize utilization and identify, assess and act on value opportunities.
• Designs rich data visualizations and uses them to communicate complex messages to business leaders at all levels of the organization, responding effectively to highly challenging questions.
• Provides ongoing visibility of projected study supply performance, costs and risk levels with clear recommendations for improvement.
• Applies strategic, cross-program knowledge of clinical supplies to positively influence clinical trial design and supply chain decisions.
• Proactively engages with internal stakeholders to identify and access novel internal and external data sources, while ensuring compliance with data security and privacy requirements. Performs & oversees techniques to validate the quality of the data, and fuse data sources using knowledge of data pre-processing techniques for complex or large-scale use cases

Basic qualifications

We are looking for professionals with these required skills to achieve our goals: 

• B.S. degree in Pharmacy, Chemistry, Biology, Engineering, Supply Chain, Logistics, Statistics, Bioinformatics, or Computer Science with 2+ years of experience

Preferred qualifications

If you have the following characteristics, it would be a plus: 

• M.S., degree in Pharmacy, Chemistry, Biology, Engineering, Supply Chain, Logistics, Statistics, Bioinformatics, or Computer Science
• Understanding of end-to-end CMC, clinical development and clinical supply forecasting, protocol development, dosing, clinical perspectives, financial analysis, risk mitigation, relevant software, data manipulation and analysis.
• Experience in strategic approaches to optimize utilization, value and risk across multiple programs and multiple modalities.
• Ability to compile, integrate and analyze data from multiple sources to answer challenging and complex business questions.
• Ability to plan and execute value measurement of data work, in order to demonstrate and improve results.
• Highly collaborative and able to advance adoption and value of advanced demand modelling through highly productive relationships with senior leaders in MDI, Clinical Development, VEO and others.
• Ability to communicate complex data science concepts and model outputs to a variety of stakeholders.
• Competency in managing matrixed and diverse teams including senior level leaders, with an emphasis on diversity, equity and inclusion.
• Highly motivated and strong capability in complex problem solving and risk management involving a range of technical quality, regulatory and operations challenges to ensure delivery to patients without compromising quality or cost.

Why GSK?

We’re combining the power of genetic and genomic insights into what causes disease, with the speed and scale of artificial intelligence and machine learning (AI/ML) to make better predictions about who a treatment might work for, and why. We believe this powerful combination of data and technology holds the key to fundamentally transforming medical discovery for the better, improving R&D success rates and shaping how even the most challenging diseases, like neurological conditions and cancer, can be both prevented and treated.

 In 2021 we delivered four major product approvals: Cabenuva for HIV, Jemperli for endometrial cancer, Xevudy for COVID-19 and Apretude, our new long-acting medicine for HIV prevention.