Sr Scientist, Molecular Biology Scientific Data

Amgen; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

Scorpion Therapeutics seeks a Senior Scientist, Business Owner for digital tools and data domains supporting molecular cloning and design across biologics discovery. Lead tool usage, workflow improvements, and data representations for sequences, constructs, plasmids, and related experiments.

Collaborate with scientists, software engineers, and data teams to implement data models, system integrations, and adoption strategies, ensuring high data quality and readiness for analytics and

Qualifications

• Hands-on cloning/construct design experience required.
• Experience translating scientific workflows into informatics tools.
• Strong data modeling, metadata knowledge, and cross-system integration familiarity.

Responsibilities

• Lead user meetings with scientists and act as point of contact for workflow/tool needs.
• Translate scientific needs into data/workflow requirements for technical teams.
• Own and evolve the scientific data domain for cloning workflows across applications.
• Define relationships/data linkages across systems and coordinate releases and adoption.

Skills

Cloning workflows

Data modeling

Cross-functional collaboration

Education

Doctorate degree

Master’s degree + 2 years experience

Bachelor’s degree + 4 years experience

Job description

What You Will Do

• Serve as the scientific Senior Scientist Business Owner for digital tools, workflows, and the data domain supporting molecular cloning and individual construct/plasmid design across biologics discovery.
• Help scientists use and improve tools for construct design, sequence registration, cloning, and related workflows.
• Own the scientific data domain for cloning workflows; define representation and connections for sequences, components, constructs, vectors, plasmids, molecule formats, and related experiments across applications.
• Partner with scientific business owners, software engineers, business analysts, and data teams on data model implementation and system integrations.

Key Responsibilities

• Lead user meetings (molecular biologists, cloning scientists, protein engineers) and act as a point of contact for workflow/tool needs.
• Translate scientific needs into data/workflow requirements; communicate complex concepts to technical teams.
• Partner through design, implementation, testing, release, and adoption; manage scope, decisions, risks, and dependencies.
• Ensure the data model supports individual construct/plasmid design and represents individual-molecule formats.
• Define scientific relationships/data linkages across applications and maintain them.
• Lead requirements reviews; coordinate training and user acceptance testing.
• Coordinate release communication, training, and adoption.
• Define standard ways of working for capturing high-quality design data.
• Improve data quality/readiness for downstream automation, analytics, and ML/AI-enabled discovery.

Basic Qualifications

• Doctorate degree
• OR Master’s degree and 2 years relevant experience
• OR Bachelor’s degree and 4 years relevant experience

Preferred Qualifications

• Degree in Molecular Biology, Protein Engineering, Structural Biology, or related field.
• Hands-on cloning/individual construct design experience; strong knowledge of molecular cloning and plasmid design workflows.
• Expertise in antibody-based molecule formats (fragments, multispecifics) and domain/architecture interpretation.
• Experience translating scientific workflows into informatics tools and implementation guidance.
• Experience owning/stewarding a scientific product/workflow/data domain/roadmap.
• Knowledge of data models, controlled terminology, metadata, identifiers, entity relationships, versioning/lineage, and cross-system integration.
• Experience with sequence design, construct registration, laboratory informatics, or similar platforms.
• Experience with requirements reviews, UAT, troubleshooting, release readiness, and adoption.
• Familiarity with agile delivery and preparing data for analytics/ML/AI.
• Strong facilitation, prioritization, problem-solving, organization, and communication across scientific and technical teams.