Process Analytics Associate Director

Overview

Follow Your Genki to North America's largest, state-of-the-art Life Science Manufacturing Facility & CDMO

The work we do at FDB has never been more important and we are looking for talented candidates to join us. We are growing our locations, our capabilities, and our teams, and looking for passionate, mission-driven people like you who want to make a real difference in people’s lives.

Join FDB and help manufacture the next vaccine, cure, or gene therapy in partnership with some of the most innovative biopharma companies across the globe.

We are proud to cultivate a culture that will fuel your passion, energy and drive - what we call Genki.

Join us

We are growing our locations and are investing more than $2 billion into establishing a new large-scale manufacturing site for biopharmaceuticals in the United States to accelerate the growth of our Bio CDMO (Contract and Development Manufacturing Organization) business.

This will be the largest end-to-end cell culture CDMO provider in North America.

The new site will offer end-to-end solutions to our customers looking to manufacture biopharmaceuticals in the US. In addition to drug substance manufacture, it will also provide automated fill-finish and assembly, packaging, and labeling services.

The new state-of-the-art facility is located in Holly Springs, North Carolina, United States.

About This Role

The Associate Director, Process Analytics is the system owner for this function, focusing on the drug substance manufacturing at FDBN.

This role sets up and maintains

informatics systems for process analytics purposes, leads projects to create new process analytics systems, and expands the capabilities and functionalities.

This role also supports Process Science for the drug substance group, and ensures the systems support the business processes in place for the site.

Additionally, this role creates multivariate models and provides training in the use of process analytics systems that are currently in place

Major Accountabilities

Builds the Process Analytics team and develops the team to deploy digital solutions for real-time process monitoring and multivariate statistical

process control

• Supervises the Analytics team and sets the direction for individual and team goals
• Leads the architecture, design, and deployment of site's process data platforms to allow machine learning models, data science applications, and

other custom applications and dashboards

• Leads the Process Analytics team in developing and maintaining internal data-focused webapps to support different stakeholders
• Seeks to continuously optimize the data management of manufacturing processes while focusing on digital solutions
• Partners with users (internal and clients) to define functional specifications and process requirements from a process data perspective,

specifically process data transmittance (sensor, control, and operation data)

Partners with users (internal and clients) for data used to support continuous manufacturing and validation, continuous improvement and

regulatory commitments

Leads innovations and systems improvement initiatives in the Process Analytics space (e.g., new in-line and on-line Process Analytical Technologies

PAT) solutions for biopharmaceutical processes with a strong focus on drug substance production process monitoring and control)

• Trains relevant stakeholders on PAT tools and respective analytical approaches (e.g., multivariate models and other statistical process methods)
• Establishes systems and procedures to enable proactive process monitoring, analysis, and reporting of manufacturing process data
• Provides team support for investigations, root cause analysis, and optimization with data support and analysis
• Functions as senior technical data leader and contact for process data, statistics, modeling, and PAT activities (e.g., automation

interface between PAT analyzers and sensors and data systems)

• Leads team in curating critical knowledge and developing best practices in Process Analytics space
• Serves as a key stakeholder in business development and defining the future large-scale operations model, including site's digital roadmap of GxP

process data

Designs and leads the development of applications and methods with model for process characterization and scale-up / out (e.g., transition

analysis to monitor column integrity, e-chromatogram review)

• Coaches and mentors’ direct reports and team members to foster professional development and growth
• Enforces and ensures team adheres to company policies and procedures
• Participates in the recruitment process to attract talent
• Collaborates with other departments (e.g., HR, Talent Acquisition) and provides input to develop retention strategies
• Addresses employee concerns and partners with HR for resolution, as needed
• Evaluates team performance and address gaps appropriately
• Other duties, as assigned

Knowledge, Skills and Abilities

• Strong knowledge of US and international regulatory standards and ICH guidelines especially with regards to data integrity
• Knowledge of PAT methodologies and implementation
• Knowledge of SIMCA-Online, TIBCO Statistical, Visual Basic and Git version control
• Strong attention to detail, highly organized, and solution-oriented mindset
• Ability to multitask in a fast-paced, highly interactive environment
• Ability to adapt communication style to differing audiences and advise others on difficult matters
• Effective communication, both written and oral
• Ability to effectively present information to others
• Ability to provide feedback to others, including leaders
• Advanced problem-solving skills
• Demonstrated ability to hire and develop top technical talent to build and lead a high performing team, projects, programs while directing

allocation of resources

Must be willing to travel domestic and international, 10-20%

Minimum Requirements

Bachelor’s degree in Engineering, Scientific or Mathematics field with

15 years of relevant experience (e.g., Statistical Control of

Manufacturing Processes or Development of Data

Collection / Management Systems); or

• Master’s degree with 12 years of relevant experience
• Previous management or supervisory experience
• Working-knowledge of structured query language (SQL) and

experience with data science and the Python data science ecosystem

e.g., NumPy, SciPy, pandas, Scikit-learn, Jupyter Notebook)

Prior experience with data mining, management and visualization,

statistical process control, and manufacturing processes

Preferred Requirements

Experience working in a Good Manufacturing Practices (GMP)

environment

Experience using IT systems to support data acquisition,

management, and evaluation

• Prior experience collaborating and interacting with a global team
• Experience with multivariate data analysis
26 days ago