Data Scientist

Amgen • Cambridge, MA

1d • $114,088 - $133,117 • Remote

About The Position

Join Amgen’s Mission of Serving Patients
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Requirements

• Master’s degree (or foreign equivalent) in Business Analytics, Engineering, Data Science or a related field & completion of a university-level course, research project, internship, thesis, or one year of experience in the following:
• Regulatory and cGMP involves authoring routine analytical reports that directly support ongoing GMP production
• Current Good Manufacturing Practices (cGMP), ICH guidelines, and Standard Operating Procedures (SOPs) to ensure analytics are performed in compliance with regulatory standards, enabling the consistent production of safe and effective medicines
• Understanding of Analytical Method Data to evaluate method performance, interpret variability, and understand the influence of method parameters to ensure appropriate statistical analysis and hypothesis development
• Product quality data obtained from lot release and in-process testing utilized to interpret data in the context of process understanding and product specifications, selecting suitable statistical tools to ensure valid analyses conclusions
• Statistical Process Control (SPC) techniques including Nelson signaling rules, process capability (Cpk) calculations, and control charting - to identify trends and detect trends in product and analytical method performance
• Statistical Analysis and Modeling to support a wide range of products and processes using statistical techniques including ANOVA, regression (including mixed-effects models), and hypothesis testing
• Data Manipulation Using SQL code to extract and organize data from electronic systems efficiently this includes developing queries to retrieve data from relational databases, ensuring integrity and readiness for statistical or analytical evaluation
• Develop and maintain code in Python and R to process, analyze, and visualize large datasets
• Utilize data engineering infrastructure, including Databricks, to integrate and transform data from multiple systems including developing efficient workflows and scalable analytics pipelines that support reproducible and automated data processing
• Communicate analytical insights effectively utilizing visualization tools including Spotfire to build dashboards and self-service analytical applications to explore data independently, visualize trends, and make informed, data-driven decisions

Responsibilities

• 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 on-going GMP activities such as the generation of the annual product review documents, regulatory inspections, and process documentation
• Stays abreast of new technologies and statistical approaches to recommend improvement

Benefits

• stock
• retirement
• medical
• life and disability insurance
• eligibility for an annual bonus or for sales roles, other incentive compensation
• Retirement and Savings Plan with generous company contributions
• group medical, dental and vision coverage
• life and disability insurance
• flexible spending accounts
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level