Senior Data Scientist

Career Category

Information Systems

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. 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.

Senior Data Scientist

What you will do

We are seeking a Senior Data Scientist to join the Technology Innovation Lab Data Science & Engineering team. Candidates should possess robust knowledge and hands-on experience in developing statistical and machine learning models and using them to drive business value. In addition to general supervised and unsupervised ML, subareas of interest include natural language processing, image & audio processing, causal modeling, time series analysis, and generative AI. Additional capabilities in mechanism-based mathematical modeling, advanced statistical modeling, or causal modeling may receive special consideration. Domain knowledge in Pharmacovigilance or at least one of biopharmaceutical R&D discipline is strongly preferred.

Let’s do this. Let’s change the world. In this vital role you will work collaboratively across disciplines with an overt sense of ownership.

• Fuel innovation and create initiatives by bringing to bear an understanding of biopharmaceutical, healthcare, and technology ecosystems.
• Be a technical guide and career development mentor to junior data scientists and machine learning engineers in a formal or matrixed fashion.
• Transform business, medical, or scientific questions into analytical ones and map out solutions, delivery, and impact.
• Communicate effectively and influence a diverse set of technical, scientific, medical, and business constituents at the functional and executive levels.
• Employ unsupervised and supervised techniques to develop predictive or prescriptive models with reliable performance, interpretability, and actionability.
• Develop or lead the deployment of generative models for a variety of applications.
• Help further build the team, including by contributing ideas and standard methodologies, and keeping abreast of developments in industry and academia.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The Data Science professional we seek will have these qualifications.

Basic Qualifications:

Doctorate degree

Or

Master’s degree and 2 years of experience in a quantitative field

Or

Bachelor’s degree and 4 years of experience in a quantitative field

Or

Associate degree and 8 years of experience in a quantitative field

Or

High school diploma/GED and 10 years of experience in a quantitative field.

Preferred Qualifications:

• Proficiency in Python and SQL.
• Experience in designing, evaluating, and applying a variety of supervised and unsupervised machine learning models to drive business value.
• Proficiency in these methodologies with demonstrated and interpretable insight and impact: Deep learning, NLP models, Time Series Models, Generative Artificial Intelligence (Gen AI), Bayesian Models.
• Experience with Healthcare data, e.g., clinical trial data, electronic medical records, and insurance claims; or Bioscience’s data, e.g., protein or small molecule data, or bioinformatics; or Biopharmaceutical manufacturing.
• Experience in Pharmacovigilance/Patient Safety strongly desired.
• Experience using causal modeling to inform decision making in a scientific, medical, or business setting strongly desired.
• Experience with cloud computing technologies, e.g., AWS, Spark.
• Experience with machine learning engineering, building and deploying modelling pipelines & APIs, and designing data models and architecture designs.
• Experience with source code control technologies, e.g., Git.
• Experience leading project teams of data scientists and machine learning engineers.
• Experience communicating tech