Sr. Pharma Business Analyst

Overview

On Site
40 - 47
Contract - W2
Contract - 6 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

Life Sciences
GxP
Genomics
Pharmaceutics
RNA
Regulatory Compliance
Pharma
Cloud Computing
Business Analysis
Business Intelligence
Data Mining
Data Governance
Manufacturing
Problem Solving
Proteomics
Requirements Elicitation
Software Development Methodology
Data Analysis
Analytical Skill

Job Details

Job Title: Sr. Pharma Business Analyst 
Job ID# 2801258
Location: Rahway NJ or West Point PA (Hybrid) (On site in either location 2 to 3 days a week a must)
Skills: Business Analysis, Data Analytics, Pharma R&D domain experience specially focused in Omics Data products (Genomics, Metagenomics, Proteomics and Metabolomics)

Must Have Experience:

  1. Functional Business Analyst coming from a Pharma / R&D / GxP environment (Who has worked in Laboratory practice or Manufacturing practice
  2. Business Analyst who has experience with Workflows, Data Mining, gathering requirements, Building Functional requirements, Writing Lifecycle Docs SDLC,
  3. Experience with Omics modalities (scRNA-seq, bulk RNA-seq, proteomics) and FAIR, Omics Data products (Genomics, Metagenomics, Proteomics and Metabolomics) would be a plus nice to have.


Mandatory Skills: Business Analysis, Data Analytics, Pharma R&D domain experience specially focused in Omics Data products (Genomics, Metagenomics, Proteomics and

  • Experience in requirements management, business analysis, and product analytics within a technical or scientific environment.
  • Familiarity with Omics modalities (scRNA-seq, bulk RNA-seq, proteomics) and FAIR data principles.
  • Strong analytical and problem-solving skills; ability to interpret technical data and translate into actionable insights.
  • Proficiency with Agile methodologies, backlog tools, and data analysis platforms (SQL, BI dashboards).
  • Help define and monitor KPIs for Omics data products (e.g., data availability, accessibility, cost efficiency).
  • Recommend optimizations for automation, scalability, and workflow efficiency.
  • Experience with cloud platforms (AWS, Azure) and data processing pipelines.
  • Exposure to AI/ML applications in Omics data analysis.

Knowledge of metadata standards, data governance, and compliance in life sciences

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