Executive Director, Bio S&T Platform, Data, Statistics & Modeling

Job Description

We are seeking an experienced senior leader to define and execute enterprise biologics process focused strategy for process platform & process data analytics, statistics, modeling and data management across the full product lifecycle (transition from R&D to commercial) for internally and externally developed & produced biologics.

The Executive Director will establish and lead a team of process experts partnering across the other Biologics S&T functions, Digital Manufacturing,  Digital CMC, R&D Biologics DS & DP development and Global Biologics Operations, and deliver on the process data strategy for biologics for driving setting up process information flows through pipeline into inline,  advanced analytics, predictive modeling/ digital twins, Electronic Lab Notebooks, Knowledge Management, and robust data governance.

This role will also lead statistics support for our Manufacturing Division.  It will report to Vice President, Biologics Science & Technology (S&T), and sit on the Bio S&T leadership team.

Key Responsibilities:

• Develop and co-own with Digital Manufacturing a multi-year digital and data strategy for biologics late-stage pipeline and inline aligned with enterprise priorities; translate strategy into a prioritized execution roadmap with clear business cases and ROI metrics., and drive execution against that roadmap.

• Establish approach and drive acceleration of adoption of analytics, statistics, modeling, AI/ML and structured content practices in Bio S&T, while holding functions accountable for execution.  This role will also be responsible for integrating across the Bio S&T functions in driving a robust knowledge management and document management strategy for CMC filings. This will be done in close integration and collaboration with Digital Manufacturing and Digital CMC.

• This role will oversee the integrated data architecture and governance model within Bio S&T that unifies process data across upstream/downstream, scale-up/tech transfer and commercial operations, including external CMOs/CDMOs.

• Serve as Bio S&T functional owner for key lab/process systems across Bio S&T (e.g ELN, utilization of VTN, KX etc); drive adoption and enable cross program learnings. Coordinate and sustain maintenance of process platforms and standards across Bio S&T functions, with functions holding content accountability.

• Identify needs, develop biologics tech business strategy for mechanistic/statistical modeling, predictive analytics, digital twins, and support NLP-enabled data extraction driving Bio S&T level execution of Digital CMC strategies, ensuring sustainability and efficiency.  Drive strong collaboration with Digital Manufacturing to link business and data science & analytics capabilities in Digital Manufacturing.

• Define, track and report KPIs for data quality, model impact, process performance (yield, cycle time, first-pass success), submission timelines and cost savings, while driving execution through Bio S&T functions.

• Drive operationalization of analytics into workflows (experimental design, tech transfer, manufacturing control, lot release) and partner with continuous improvement teams to capture efficiencies.  Integrate at site technology process data leads and above site process data leads driving to efficient and sustainable execution of overarching biologics data strategy and process monitoring.

• Oversee and streamline statistics support & training across Manufacturing process and analytical working groups, and functions.

• This role will partner very closely with Digital Manufacturing and Digital CMC to drive an integrated strategy for biologics across Bio S&T functions.  This team will integrate existing local efforts on data management, data strategy, modeling, statistics, data sciences within Bio S&T

• Drive change and adoption of data and digital mindset within Bio S&T across all functions and all levels of the organization.

• Recruit, develop and retain a multidisciplinary team; champion inclusive talent management and succession planning.

Education:

• Bachelor's degree (PhD preferred) in biochemical/chemical engineering, computational biology, biostatistics, data science or related field.

Required Experience and Skills:

• 10+ years industry experience in biologics process development, manufacturing, CMC or related functions, with substantial experience leading enterprise digital/data transformation.

• Demonstrated experience building COEs or comparable cross-functional organizations, implementing enterprise data strategies and integrating external manufacturing