Data Analyst – Process Monitoring & Data Sciences

As a Data Analyst – Process Monitoring & Data Sciences, you will support the development and digital integration of process performance and product quality monitoring capabilities. You will work at the intersection of bioprocessing, data analytics, and digital technology to transform manufacturing and process data into actionable insights. The role combines data quality, analytics, automation, dashboard development, and scientific problem-solving. You will help modernize monitoring strategies, improve data reliability, and streamline workflows used by scientists and engineers. Working across technical and scientific teams, you will contribute to projects from initial concept through delivery. This fully remote opportunity is well suited to a quantitatively minded professional interested in applying data and technology to biopharmaceutical processes.

• Bachelor's degree in Engineering, Computer Science, Mathematics, Statistics, Life Sciences, or another quantitative discipline.
• Alternatively, an Associate degree with 4 years of relevant experience, or a high school diploma/GED with 6 years of relevant experience.
• Previous experience in the pharmaceutical, bioprocessing, biotechnology, or related life sciences industry.
• Experience in process development, clinical or commercial manufacturing, attribute sciences, quality control, or another relevant biopharmaceutical function is preferred.
• Familiarity with one or more data and analytical technologies such as SQL, Python, R, Databricks, Spotfire, Tableau, SIMCA, Aveva PI, DeltaV, or Dassault Systèmes platforms.
• Familiarity with AI-assisted development tools such as Codex or Claude is beneficial.
• Experience with statistical analysis, data visualization, data engineering, application development, or AI-enabled development tools is advantageous.
• Strong quantitative and analytical problem-solving abilities, with careful attention to data quality and detail.
• Intellectual curiosity and the ability to learn new scientific and technical concepts quickly.
• Ability to work effectively across scientific, technical, and business functions.
• Strong organizational skills and the ability to manage multiple priorities while working through ambiguous problems.
• Ability to independently develop practical solutions, communicate effectively with stakeholders, and incorporate feedback to continuously improve results.