Scientific Business Analyst (Specialist) - R&D Omics

Scientific Business Systems Analyst

Roles & Responsibilities

• Requirements & Analysis:

  Function as a

  Scientific Business Systems Analyst

  within a

  Scaled Agile Framework (SAFe)

  product team. You will serve as a liaison between global Research Informatics and research scientists, translating complex scientific needs into clear, actionable requirements and user stories.

• Platform & Technology Management:

  You will manage a suite of custom internal platforms,

  Commercial Off-the-Shelf (COTS)

  software, and system integrations. You will stay updated with industry trends, technological advancements, and scientific progress in

  Omics

  techniques.

• Product Roadmap & Risk Management:

  Develop and maintain a product roadmap that outlines planned features, enhancements, and timelines. You will also be responsible for identifying and managing technological risks, scientific validation, and user acceptance.

• Compliance & Innovation:

  Ensure operational excellence, cybersecurity, and compliance. You will also ensure that scientific data operations are scoped into building Research-wide

  Artificial Intelligence/Machine Learning (AI/ML)

  capabilities.

• Collaboration & Support:

  Collaborate with geographically dispersed teams, foster a culture of collaboration and innovation, and develop documentation, communication plans, and training for end users.

Technical Skills

• Expertise in

  Omics data

  (Genomics, Proteomics, Transcriptomics, etc.) and oncology data.
• Experience with bioinformatics tools and research workflows used to manage omics data.
• Good understanding of database technology (e.g.,

  RDBMS, Databricks

  ).
• Experience with writing user requirements and acceptance criteria in agile project management systems like

  JIRA

  .
• Experience with cloud (

  e.g., AWS

  ) and on-premise infrastructure.
• Experience using platforms such as

  Spotfire, Tableau, Power BI

  , etc., to build dashboards and reports is a plus.
• Knowledge of handling

  GxP

  data and system validation (i.e.,

  GCP

  ) is a plus.
• Understanding of

  AI

  and

  machine learning

  for drug discovery research is a plus.
• Experience with platforms such as

  Benchling

  or other

  LIMS

  is a plus.

Qualifications

• A Ph.D. with relevant experience, a Master's degree with extensive experience, a Bachelor's degree with a substantial background, or a Diploma with a significant amount of experience in a Life Sciences, Computer Science, or a related field.
• Experience in implementing and supporting biopharma scientific software platforms is preferred.

• SAFe for Teams

  certification is preferred.

Soft Skills

• Problem-Solving:

  Excellent analytical and gap/fit assessment skills.

• Communication:

  Strong verbal and written communication skills, with the ability to present effectively to various audiences.

• Proactiveness:

  A high degree of initiative and self-motivation, with the ability to work under minimal supervision and manage multiple priorities successfully.

• Collaboration:

  Team-oriented, with a focus on achieving team goals and the ability to work effectively with global, virtual teams.

• Adaptability:

  The ability to stay updated with industry trends and technological advancements.