CDnA - Senior Data Scientist

Career Category

Sales & Marketing Operations

Job Description

Job Description

HOW MIGHT YOU DEFY IMAGINATION?

You’ve worked hard to become the professional you are today and are now ready to take the next step in your career. How will you put your skills, experience and passion to work toward your goals? At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies, reaching over 10 million patients worldwide. Come do your best work alongside other innovative, driven professionals in this meaningful role.

CDnA - Senior Data Scientist

Live

What you will do

Let’s do this. Let’s change the world. Are you passionate about using machine learning to shape the future of healthcare? In this vital role you will be leveraging cutting edge artificial intelligence tools and technology to influence decisions across the organization.

This role requires extensive knowledge of machine learning, the creativity to identify opportunities for data science to be impactful, and deep expertise with the complexities of life sciences data. You will create solutions and insights to solve challenging business problems across multiple therapeutic areas and commercial functions. The Senior Data Scientist will own the complete project lifecycle, from ideation to deployment. This individual will apply their deep technical expertise to manipulate large messy datasets, write high-quality code, and adapt complicated machine learning models to the problems at-hand. The Senior Data Scientist should be well versed in moving models from development to production and have a good sense for tracking and updating model performance. Most importantly, this individual is a strong storyteller, and will distill complicated technical work to understandable and actionable outputs.

Some projects that the Senior Data Scientist will support include physician targeting and segmentation, lead generation for our field sales teams, patient journey mapping and prediction, disease incidence and prevalence projection, and predicting patients likely to start therapy.

Flexible Commuter role to Deerfield, IL office. You will work on-site a minimum of 2 days a week.

• 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 action-ability.
• 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.

Win

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The professional we seek is analytical with 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:

• Experience in designing, evaluating, and applying a variety of supervised and unsupervised machine learning models to drive business value
• Proficiency in state-of-the-art machine learning tools, such as deep learning frameworks, transformer models, NLP models, time series models, generative artificial intelligence (Gen AI), and Bayesian models, with demonstrated and interpretable insight and impact
• Deep programming expertise with Python and related ML libraries like scikit-learn, MLib, TensorFlow, or PyTorch
• Familiarity with the modern data stack: distributed computing tools (Spark, Hive, etc.), cloud computing environments, and source code control technologies (e.g. Git)
• Full stack experience with building and deploying data engineering or modeling pipelines
• Experience leading project teams of data scientists and machine learning engineers
• Excellent organization/planning skills and talent for lead