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# Data Scientist

- **Company:** Amgen
- **Location:** Cambridge, MA, United States (Remote available)
- **Salary:** $114,088.0 - $133,117.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Data Analysis, Business Intelligence Development, Computer Engineering, Data Warehousing, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Natural Language Processing, Snowflake, Deep Learning, Convolutional Neural Networks, Data Analytics, Data Pipelines, Amazon Redshift, Databricks, Programming Languages
- **Published:** September 2, 2026
- **Apply:** https://www.biospace.com/logon?PipelinedPage=%2Fjob%2F3071956%2Fdata-scientist%3FAction%3DContinueJobApplication%23application-form

## About the Role

Requirements: Position requires a Masters degree (or foreign equivalent) in Data Science, Computer Engineering or related field & completion of a university-level course, research project, internship, thesis, or one year of experience in the following:

Data analysis and visualization using tools including Power BI and Tableau

Develop data pipelines Extract, Transform, and Load using Data warehouse solutions including Databricks, Snowflake, and Amazon Redshift

Analyze time series data and performing statistical analyses and hypothesis testing;

Programming languages including Python and R;

AI/ML (Artificial Intelligence/Machine Learning) techniques including classification, regression, and anomaly-detection methods for predictive analytics and operational improvements;

Conducting research in AI/ML (Artificial Intelligence/Machine Learning) topics including deep learning, natural language processing (NLP), and predictive analytics for potential application; and

Machine Learning models including convolutional neural networks to understand protein structures.

## Description

Duties: Apply statistical trending tools to product and method data Apply engineering principles and multivariate statistical analysis in-order to understand sources of variation and evaluate opportunities for improvements; Use data analytics software to develop visualizations to review, assess, and improve analytical method performance; Interface with analytical scientists, process development scientists, and engineers to assess, understand, and support data consumption needs; Interface with product quality, QC, quality assurance, and manufacturing organizations to resolve method issues; Support ongoing GMP activities such as the generation of the annual product review documents, regulatory inspections, and process documentation; Stay abreast of new technologies and statistical approaches to recommend improvement; and Apply machine learning methodologies where appropriate for analyzing datasets. May telecommute.


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