Remote Data Analyst - Process Monitoring & Data Science

Dale Workforce Solutions; Providence (RI); Remote; USD 114,616,000 - 128,943,000; Full time

Job summary

Global Biotech Company is seeking an Associate Data Analyst for remote work across the US to support PPPQM capabilities. The role sits at the intersection of bioprocessing, data analytics, and digital technology, using manufacturing data to enable monitoring and actionable insights for scientists and engineers.

Ideal candidates have a quantitative background and curiosity about data; experience in process development or QC is a plus, and there is emphasis on building robust data workflows and

Qualifications

• Experience in pharmaceutical, bioprocessing, or biotechnology industry.
• Bachelor’s degree in a quantitative field (engineering, CS, math, etc.).
• Familiarity with data/analytic technologies such as SQL, Python, R, Databricks, Spotfire/Tableau, SIMCA, Aveva PI, DeltaV, or Dassault Systèmes.

Responsibilities

• Execute PPPQM analytics, APR analytics, and monitoring deliverables.
• Support migration and digitalization of monitoring strategies to new software.
• Ensure data quality and pipeline integrity with QA checks.
• Analyze large datasets using SQL, Python/R, Spotfire/Tableau.
• Develop and maintain dashboards, models, and data products.
• Troubleshoot analytics and digital solutions for robustness.
• Explore AI and advanced analytics to improve workflows.
• Collaborate cross-functionally to translate needs into data solutions.

Skills

SQL

Python/R

Spotfire/Tableau

SIMCA

Aveva PI

DeltaV

Dassault Systèmes

Databricks

Education

Bachelor's degree

Associate degree

High school diploma/GED

Tools

Databricks

Power BI

Tableau

Job description

Global Biotech Company is seeking an Associate Data Analyst for remote work across the US to support PPPQM capabilities. The role sits at the intersection of bioprocessing, data analytics, and digital technology, using manufacturing data to enable monitoring and actionable insights for scientists and engineers.

Ideal candidates have a quantitative background and curiosity about data; experience in process development or QC is a plus, and there is emphasis on building robust data workflows and