Scientific Data Architect - Biologics Manufacturing & Quality Control

TetraScience • Boston, MA

7d • $140,000 - $240,000

About The Position

As a Scientific Data Architect supporting TetraScience’s partnership with a top 25 global biopharma manufacturing and quality organization, you will design scientific data models and use cases that connect manufacturing processes, laboratory results, and product quality across manufacturing sites and external partners. Your work will support investigations, continued process verification (CPV), process improvement, technology transfer, and the application of AI to biologics manufacturing.

You will combine biologics manufacturing and quality-control knowledge with the technical ability to design, prototype, and implement scientific data solutions. Working directly with manufacturing scientists, MSAT, manufacturing IT, QC, Quality Assurance, data engineers, and product teams, you will translate scientific and operational questions into explicit data requirements, reusable models, and practical applications. You will take ownership from site discovery through implementation and adoption, including writing code, examining source data, testing assumptions with scientific users, and demonstrating working solutions. The role requires willingness and ability to travel up to 50% of working time between partner manufacturing sites.

You will lead discovery, develop reusable biologics product, process, and QC data models, connect batch and material genealogy with process and QC results, and reconcile data across sites and external manufacturing partners while retaining source provenance. You will build use cases for investigations, CPV, cross-batch comparisons, process and yield analysis, and technology transfer. You will develop Python parsers, transformations, quality checks, and applications using Tetra OS; prepare contextualized datasets for statistical, mechanistic, and AI/ML models; and support verification and validation within partner Quality processes. You will demonstrate solutions, incorporate user feedback, and train partner teams to maintain and extend delivered models and applications.

TetraScience describes itself as the Scientific Data and AI Company building Tetra OS, an operating system for scientific intelligence. Its mission is to help life sciences firms turn fragmented scientific data into AI-native assets and workflows that accelerate discovery, development, and manufacturing. Candidates are asked to review “The Tetra Way” as part of the application and interview process. Visa sponsorship is not currently provided for this position. The salary range is $140,000–$240,000; final compensation depends on factors including experience, localized market data, and internal team equity.

Requirements

• Minimum 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.

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.
• Record of 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 systems such as 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; 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, establishing shared structures and controlled vocabularies while retaining 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 preserving 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 with documented requirements, source-to-target mappings, test evidence, and reproducible analyses within partner Quality processes.
• Regularly demonstrate solutions, incorporate user feedback, and train partner teams to maintain and extend delivered models and applications.
• Travel between partner manufacturing sites for discovery, implementation, workshops, training, and adoption support, up to 50% of working time.

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 you can grow your career and get coaching

What This Job Offers

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