Senior Business Analyst, Scientific

Cambridge, MA

Description

Verista's 500 experts team up with the world's most recognizable brands in the life science industry to solve their business needs. The nature of our business is to empower growth and innovation within the scientific community and to help researchers, organizations, and companies solve some of the world's most pressing healthcare challenges. Verista provides innovative solutions and services that empower informed decision-making and are the result of our significant investment in our people and our capabilities.

Our ability to grow is driven by world-class people who thrive in a team environment and share our mission to enable life sciences clients to improve lives. Our talented and dedicated professionals are committed to making an impact every day.

Company Culture Guidelines & Values:

• We empower and support our colleagues
• We commit to client success at every turn
• We have the courage to do the right thing
• We encourage an inclusive environment where our colleagues feel respected, engaged, and challenged.
• We constantly acquire new skills and learn from our experiences to enhance our collective expertise

Job Overview: We are seeking an experienced Senior Business Analyst with a successful project track record working directly with scientists on scientific applications. This role bridges the laboratory and the technology platform, translating scientific workflows into well-defined requirements and configurations that help scientists work effectively and feed high-quality data into the enterprise data lakehouse. The analyst will support initiatives across entity registration, sample and inventory management, electronic lab notebooks, assay and method registration, instrument data capture, and lab automation, working with both chemistry and biologics teams.

Key Responsibilities:

• Partner with scientists and laboratory teams to elicit, document, and prioritize business and scientific requirements for laboratory applications and platforms.
• Lead requirements and workflow analysis for entity registration and end-to-end sample and inventory management, including sample tracking, storage, and lifecycle workflows.
• Support electronic notebook (ELN) implementations, going beyond rollout to design and validate configurations, templates, and structured data capture that make scientists more effective and deliver quality data to the data lakehouse.
• Support assay and method registration system implementations, defining data models, metadata standards, and registration workflows with scientific stakeholders.
• Define requirements for automated instrument data capture and integration, working with scientists, IT, and vendors to move instrument data reliably into downstream systems.
• Support lab automation and workflow automation efforts, including lab-in-the-loop programs, by mapping current-state processes, identifying automation opportunities, and defining future-state workflows.
• Translate scientific needs into functional specifications, user stories, and acceptance criteria, and coordinate with developers, vendors, and configuration teams through design, build, testing, and deployment.
• Facilitate user acceptance testing, training, adoption, and post-go-live support, tracking the value realized from delivered solutions.
• Serve as the liaison between chemistry and biologics teams, IT, data, and platform teams, managing stakeholder expectations, dependencies, risks, and project status.

Requirements:

• Bachelor's degree in Life Sciences, Chemistry, Biology, Computer Science, Information Systems, or a related field; advanced degree a plus.
• 7+ years of experience as a business analyst, with a successful project track record delivering scientific or laboratory applications for R&D scientists.
• Hands-on experience in several of the following areas: entity registration, sample/inventory management, ELN implementation, assay/method registration, instrument data capture and integration, and lab automation.
• Experience with sample management, workflow automation, and automated instrument data capture, plus demonstrated experience realizing value from ELN beyond initial rollout, including building configurations that improve scientist workflows and data quality.
• Domain experience in chemistry or biologics, ideally with baseline familiarity in both to support conversations with each team.
• Familiarity with data lakehouse or scientific data platform concepts, including data quality, metadata, and FAIR…