Director of Data Management & Analytics

Advanced Regenerative Manufacturing Institute•Manchester, NH

About The Position

The Director of Data Management & Analytics is a strategic and technical leader responsible for defining and executing the organization’s data strategy. The role connects scientific research with scaled, automated manufacturing by overseeing data infrastructure—including ingestion, governance, and architecture—and advanced analytics such as predictive modeling, statistical analysis, and machine learning. These capabilities support scientific discovery, cell therapy production, chain-of-custody and chain-of-identity tracking, and regulatory submissions. The Director leads the integration of complex data across R&D, preclinical development, manufacturing (CMC), supply chain and logistics, and commercial operations. The role establishes data strategy and governance, develops the data platform and analytics capabilities, leads and mentors multidisciplinary data teams, and partners with technical, scientific, operational, regulatory, and executive stakeholders. The position also evaluates emerging technologies and manages relationships with external vendors and technology partners. The Advanced Regenerative Manufacturing Institute (ARMI)/BioFabUSA is a member-based, member-driven nonprofit public-private partnership focused on advancing the bioeconomy and transforming the future of human health. It provides technical and commercialization services to companies advancing technologies that contribute to this mission.

Requirements

Bachelor’s degree in Data Science, Biostatistics, Bioinformatics, Life Sciences, Computer Science, or a related field.
5–8+ years of progressive experience in data architecture, data engineering, and advanced analytics, including at least 4+ years in life sciences, biotech, pharma, or cell/gene therapy ecosystems.
3–5+ years of direct management experience leading cross-functional data teams.
Demonstrated experience building enterprise data governance, architecture, and analytics capabilities from the ground up.
Advanced command of statistical tools and programming, including Python, R, SQL, and SAS.
Deep experience with modern cloud data systems such as Azure, Snowflake, or AWS.
Familiarity with R&D and manufacturing or biomanufacturing data systems, including ELN, MES, LIMS, and ERP.
Track record of leading and scaling high-performing data and analytics teams.
Strong communication and presentation skills, including experience presenting to senior leadership.

Nice To Haves

An advanced degree (MS or PhD) is strongly preferred.
Direct cell therapy or advanced therapy medicinal product (ATMP) experience is strongly preferred.
Experience with autologous or allogeneic cell therapy manufacturing and chain-of-identity or chain-of-custody data systems.
Familiarity with mass spectrometry-based multi-omics, single-cell genomics, flow cytometry, and other cell characterization data types.
Experience implementing AI/ML solutions in a regulated life sciences environment.
Experience in a high-growth, fast-paced biotech environment, including clinical-to-commercial transition.

Responsibilities

Define and drive the technical data strategy and roadmap, aligning data and analytics investments with R&D, manufacturing, and commercial priorities.
Advise the Executive Team on data-driven opportunities and risks.
Build, mentor, and lead a high-performing team of data engineers, data scientists, bioinformaticians, and data governance and quality specialists.
Establish the organization’s data culture and promote data literacy and evidence-based decision-making across functions.
Oversee the design and implementation of a unified data platform or data lake integrating data from R&D, preclinical development, manufacturing, supply chain, and commercial operations.
Partner with IT and Digital leadership on cloud infrastructure, data pipelines, interoperability standards, and system integrations.
Establish enterprise data governance policies, standards, and stewardship models to support data integrity, quality, security, and phase-appropriate regulatory compliance.
Lead data privacy and security initiatives in partnership with IT Security and Legal.
Promote advanced analytics, machine learning, and AI to accelerate scientific discovery, optimize manufacturing yield and process parameters, and predict supply chain risk.
Enable predictive and prescriptive analytics for manufacturing process optimization and capacity planning.
Evaluate and implement emerging technologies, including AI/ML platforms, digital twins, and real-world data and evidence tools.
Collaborate with R&D, Manufacturing/CMC, Quality, Regulatory Affairs, Supply Chain, and Commercial teams to understand data needs and deliver fit-for-purpose solutions.
Partner with the Executive Team, where applicable, on technology infrastructure decisions and IT roadmap alignment.
Manage relationships with external vendors, data platform providers, and technology partners.