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Omics Data Automation Jobs (NOW HIRING)

Merck & Co.

... omics data-generation.-Candidates who have-demonstrated-the ability to design-and-execute-high throughput-translational studies-with human biospecimens at-scale and-leveraging-automation to enable ...

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Omics Data Automation information

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How much do omics data automation jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for omics data automation in the United States is $16.01, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $16.83 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Omics Data Automation Specialist, and why are they important?

To thrive as an Omics Data Automation Specialist, you need a solid background in bioinformatics, data analysis, and molecular biology, often with a relevant degree such as bioinformatics, computational biology, or a related field. Proficiency with scripting languages (e.g., Python, R), workflow management systems (e.g., Nextflow, Snakemake), and experience using cloud platforms and automation tools are essential. Strong problem-solving skills, attention to detail, and effective communication help professionals collaborate effectively and adapt to rapidly evolving technologies. These skills are crucial for handling large-scale omics datasets efficiently, ensuring reproducibility, and accelerating scientific discovery.

What are the typical challenges faced when automating omics data workflows, and how can they be addressed in this role?

Automating omics data workflows often involves handling large, complex datasets from genomics, proteomics, and other 'omics' disciplines, which can create challenges around data standardization, integration, and quality control. In this role, you may encounter issues such as inconsistent file formats, varying data quality, and the need to ensure reproducibility and scalability of analysis pipelines. Addressing these challenges typically requires strong programming skills, familiarity with bioinformatics tools, and close collaboration with both biologists and IT teams to ensure that automated solutions meet scientific and technical requirements. Continuous learning and staying updated on best practices in data management are also essential.

What is Omics Data Automation?

Omics Data Automation refers to the use of advanced computational tools and workflows to manage, process, and analyze large-scale biological data sets from omics fields such as genomics, proteomics, transcriptomics, and metabolomics. This automation streamlines repetitive data handling tasks, improves reproducibility, and accelerates research by integrating data from multiple sources. It is crucial for modern life sciences, where data volume and complexity exceed what can be managed manually, enabling more efficient discoveries and insights.
Sr. Pharma Business Analyst

Sr. Pharma Business Analyst

Noblesoft Technologies

Rahway, NJ • On-site

$93K - $121K/yr

Contractor

Posted 3 days ago

Job description

Job Title: Sr. Pharma Business Analyst 
Location: Rahway NJ or West Point PA
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