GSK is currently looking for a Sr. Digital and Data Science MSAT Manager to join our team in Upper Merion, PA. The Manufacturing Science and Technology (MSAT) organization is a site-based technical team responsible for ensuring manufacturing processes are capable, compliant and productive while maintaining product quality.  The site MSAT team is also responsible for delivering continuous improvements to the existing supply chains supported by UM Biopharm and working with global MSAT to execute technology transfers and implement process-related improvement programs across the product lifecycle.

The Senior Manager MSAT, Digital Systems and Processes serve as the site MSAT leader in the data and analytics space, supporting site initiatives and implementation of smart manufacturing principles in collaboration with the site digital and analytics teams and driving innovative solutions to complex technical problems. The Senior Manager will lead a team of data scientists and engineers to facilitate delivery of product and process data solutions in biologics manufacturing environment. This team will leverage data as a key asset to accelerate technology transfer and simplify validation processes, support continuous improvement for established commercial processes, and enhance technical understanding of biopharmaceutical manufacturing.

The Senior Manager will be expected to support technical development of the MSAT organization, promoting technical and leadership capability to develop a high performing MSAT team and improving the data literacy and capability of the MSAT organization. The Senior Manager is also expected to manage within a matrix team to ensure alignment of data analytics platforms and approaches, collaborating with team members from other UM Biopharm departments (i.e. production, quality, engineering) and with stakeholders in central MSAT, data, and analytics teams to drive implementation of novel data analytics tools and technologies into the commercial manufacturing space.

Key Responsibilities:

• Serve as the technical enterprise leader for data science and analytics capabilities for the MSAT team at UM Biopharm to deliver acceleration and simplification of new product introduction and robust commercial manufacturing for GSK supply chain and patients.
• Accountable for the development and deployment of the strategic data and analytics plan for the UM MSAT Team, in collaboration with other site and central digital and analytics teams.
• Drive innovation through leading continuous improvement for technical processes or systems and championing introduction of novel technologies, including new modeling platforms and approaches (first-principle modeling, CFD, machine learning), digital systems and visualizations, and process analytical technologies (PAT).
• Lead a team of scientists and engineers to work collaboratively and efficiently to deliver the technical objectives. Support capability development of the MSAT team to learn/implement new analytical technologies and modeling systems.

Why you?

Basic Qualifications:

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

• BS/BA degree in either biological or chemical science or engineering or equivalent technical discipline with a minimum of 5 years of experience in the Biopharmaceutical/pharmaceutical industry OR MS or PhD degree with a minimum of 3 years of experience in the biopharmaceutical/pharmaceutical industry.

Preferred Qualifications:

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

• MS or Ph.D. in data/computer science or engineering, biological or chemical science or engineering or equivalent technical discipline. 
• In-depth experience with digital, data, and analytics techniques in the pharmaceutical industry. Specific experience or knowledge of biopharmaceutical manufacturing (upstream / downstream) is preferred.
• Experience with industrialization or implementation of models in a GMP environment, including development of model lifecycle management framework and integration into regulatory filings is preferred
• Familiarity and experience with relational databases, statistical softwares (i.e. SAS, SIMCA), modeling and visualization softwares (i.e. Python, R, Matlab, MS Power). Experience of developing or applying techniques such as pre-processing, classification, regression, clustering, dimensionality reduction and model selection.
• Experience with manufacturing / engineering environments including systems such as IP-21, M-ERP, LIMS, Aspen eBRs.
• Knowledge of GMPs and major regulatory agency regulations, specifically as they relate to data science or data validation.
• Strong interpersona