Data Scientist
Amgen
- Location
- United States - Remote
- Work model
- Remote
- Level
- Mid
- H-1B history
- 137 approvals (FY2023)
- Posted
- 23h ago
Skills
About this role
Career Category Research Job Description 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. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. 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. Data Scientist As a Data Scientist , you will design, develop, and implement scalable data engineering, machine learning (ML), and analytics solutions that accelerate Clinical Development and advance therapies for patients. You will act in support the Center for Design & Analysis, partnering with data scientists and cross-functional teams to translate business requirements into robust data pipelines, analytical tools, and visualization solutions. You will contribute to the implementation and continuous improvement of innovative analytics capabilities, helping to optimize methods, algorithms, and processes while ensuring solutions are reliable, scalable, and aligned with Amgen's quality and compliance standards.
Responsibilities
Collaborating with research scientist and other data scientists to develop AI and advanced analytics solution to speed drug research and development. Designing, writing, and testing data / ML pipelines and other advanced analytic / visualization solutions Collect business requirements / user stories for new or enhancements to existing analytic solutions Train users in the use of solutions provided by the CfDA Data Science organization Contribute to process improvement initiatives Adhere to Amgen Policies, SOPs, and other controlled documents. Participate in the development and review of CfDA Data Sciences Policies, SOPs, and other controlled documents. Participate in external professional organizations, conferences and/or meetings. Accountabilities: Contribute to the implementation of internally developed and externally provided analytic solutions Participate in the development of innovative and effective approaches to solve client's analytics problems and communicate results & methodologies Recommend ongoing improvements to methods and algorithms that generate analytic insights Win What we expect of you We are all different, yet we all use our unique contributions to serve patients.
Basic Qualifications
Ph.D. degree OR Master’s degree 2 years of related experience Preferred Qualifications MS or PhD in Statistics/Biostatistics, Mathematics, Computer Science, Data Science, Physics, Informatics, Life Sciences, or quantitative related field. A proven ability to write robust code in R / Python A working understanding of common machine learning algorithms and approaches (NNs, RF classifiers, Ensemble methods, NLP etc.) and when to use them. Proficiency in Linux operating system and associated shell commands. Experience working effectively in a globally dispersed team environment. Drug Development (pre-, early, late and/or observational) in related industries or academic research) Experience working with: Distributed compute / data technology (e.g., Spark, Python Dask) DevOps frameworks (e.g., Git) Building and deploying analytic solutions in a