Scientific Data Architect - Biologics Manufacturing & Quality Control at TetraScience in Boston, MA

Job description

About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “ The Tetra Way ,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. As a Scientific Data Architect supporting our partnership with a top 25 global biopharma manufacturing and quality organization, you will design the 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Candidates will be asked to review “The Tetra Way” as part of the interview process. Who You Are You combine deep experience in biologics manufacturing and quality control with the technical ability to design, prototype, and implement scientific data solutions. You understand how a manufacturing process generates data, how QC laboratories test for product quality, and how to preserve the relationships between those records. You are comfortable working directly with manufacturing scientists, Manufacturing Sciences and Technology (MSAT), manufacturing IT, QC, Quality Assurance, data engineers, and product teams. You translate their questions into explicit data requirements, reusable models, and applications they can use in daily work. You take ownership from initial site discovery through implementation and adoption. You write code, examine source data, test assumptions with scientific users, and demonstrate working solutions. You have the willingness and ability to travel up to 50% of working time between partner manufacturing sites for discovery, implementation, workshops, training, and adoption support. Requirements What You Have Done What you must bring A minimum of 3-5 years direct experience in biologic drug manufacturing and QC is required, including substantial experience with monoclonal antibodies or other recombinant therapeutic proteins. You have designed data models and delivered analytical or digital use cases using manufacturing and QC data for these modalities. Strong Python and SQL skills, with 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. Desired: Manufacturing & Quality Relevant life sciences industry experience, with substantial work in biologics manufacturing, process development, MSAT, analytical development, or QC. Demonstrated 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, continued process verification (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 c