Scientific Data Architect - Biologics Manufacturing & Quality Control

TetraScience • Boston, MA

6d

About The Position

TetraScience is the Scientific Data and AI Company building Tetra OS, an operating system for scientific intelligence. The company helps life sciences firms turn fragmented scientific data into AI-native assets and workflows that accelerate discovery, development, and manufacturing.

The Scientific Data Architect will support a partnership with a top 25 global biopharma manufacturing and quality organization. The role designs scientific data models and use cases connecting manufacturing processes, laboratory results, and product quality across manufacturing sites and external partners. The work supports investigations, continued process verification (CPV), process improvement, technology transfer, and the application of AI to biologics manufacturing.

The architect combines biologics manufacturing and quality-control experience with the technical ability to design, prototype, and implement scientific data solutions. The role involves working with manufacturing scientists, MSAT, manufacturing IT, QC, Quality Assurance, data engineers, and product teams; translating questions into data requirements, reusable models, and practical applications; and taking ownership from site discovery through implementation and adoption. The position requires willingness and ability to travel up to 50% of working time between partner manufacturing sites.

The role leads discovery, develops reusable product, process, and QC data models, connects manufacturing and QC records across systems, and builds analytical use cases. It also includes developing Python-based data solutions, collaborating on integrations and data products, preparing datasets for statistical, mechanistic, and AI/ML models, supporting verification and validation, demonstrating solutions, and training partner teams. Candidates will be asked to review “The Tetra Way” during the interview process. Visa sponsorship is not currently provided for this position.

Requirements

• At least 3–5 years of direct experience in biologic drug manufacturing and QC, including substantial experience with monoclonal antibodies or other recombinant therapeutic proteins.
• Experience designing data models and delivering analytical or digital use cases using manufacturing and QC data for these modalities.
• Strong Python and SQL skills.
• Experience developing parsers, transformations, APIs, and analytical applications using tabular and JSON data.
• Ability to communicate architecture decisions and scientific findings to laboratory users, manufacturing teams, engineers, and business leaders.
• Willingness and ability to travel up to 50% of working time between partner manufacturing sites for discovery, implementation, workshops, training, and adoption support.

Nice To Haves

• Relevant life sciences industry experience, with substantial work in biologics manufacturing, process development, MSAT, analytical development, or QC.
• Understanding of upstream and downstream biologics operations, including cell culture, harvest, chromatography, filtration, and drug-substance production, and how process conditions relate to yield and quality.
• Experience defining and implementing manufacturing or QC use cases such as batch investigations, CPV, yield analysis, raw-material variability assessment, stability trending, or technology transfer.
• Experience delivering solutions in GxP environments, including traceability, data integrity, controlled changes, reproducible calculations, and collaboration with Quality and Validation teams.
• Experience designing conceptual, logical, and physical data models connecting products, batches, material lots, process steps, equipment, samples, analytical results, and quality events across systems.
• Experience integrating scientific and manufacturing data from LIMS, laboratory instruments, process historians, MES, ERP, ELN, and quality management systems.
• Experience with multi-site manufacturing data harmonization and external CMO/CDMO data integration.
• Experience with process historian and time-series data, chromatography data, statistical process monitoring, and multivariate analysis.
• Experience with Databricks, cloud data platforms, and manufacturing information models such as ICH, ISA-88, and ISA-95.

Responsibilities

• Lead onsite discovery with manufacturing, MSAT, QC, IT, and Quality teams alongside the Scientific Business Analyst; map workflows, inspect source data, identify gaps, and define prioritized use cases with measurable outcomes and acceptance criteria.
• Design reusable product, process, and QC data models for biologics manufacturing with the platform knowledge engineering team, balancing shared structures and controlled vocabularies with product-, modality-, and site-specific requirements.
• Model batch and material genealogy, including splits, pools, intermediate lots, and links between drug substance and drug product.
• Connect process measurements and QC results to the appropriate batch, unit operation, sample, method version, and specification.
• Define mappings across sites and external manufacturing partners, reconciling identifiers, terminology, units, timestamps, and process hierarchies while retaining source provenance.
• Build use cases for investigation evidence assembly, CPV, cross-batch comparisons, process and yield analysis, and technology transfer.
• Translate scientific questions into data requirements, calculations, prototypes, and production-ready specifications.
• Develop Python parsers, data transformations, quality checks, and applications using Tetra OS.
• Collaborate with engineering teams to deliver reliable integrations and maintainable data products.
• Prepare contextualized datasets for statistical, mechanistic, and AI/ML models.
• Work with scientific users and applied AI engineers to assess data suitability, interpret outputs, and evaluate performance.
• Support verification and validation through documented requirements, source-to-target mappings, test evidence, and reproducible analyses within partner Quality processes.
• Demonstrate solutions regularly, incorporate user feedback, and train partner teams to maintain and extend delivered models and applications.

Benefits

• 100% employer-paid benefits for all eligible employees and immediate family members.
• Unlimited paid time off (PTO).
• 401K.
• Company-paid life insurance and LTD/STD.
• A culture of continuous improvement where employees can grow their careers and receive coaching.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed