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Senior Principal Scientist, Data Analytics and Pharmacometric Modeling - Thousand Oaks California
Company: Amgen Inc. (IR)
Location: Thousand Oaks, California
Posted On: 11/07/2024
Senior Principal Scientist, Data Analytics and Pharmacometric Modeling Career Category: Scientific Location: US - California - Thousand Oaks Job Type: Full time Posted: 2 Days Ago Job Requisition ID: R-187174 HOW MIGHT YOU DEFY IMAGINATION? If you feel like you're part of something bigger, it's because you are. 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. We are global collaborators who achieve together-researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It's time for a career you can be proud of. What you will do: The Clinical Pharmacology, Modeling & Simulation Department at Amgen is seeking a Senior Principal Scientist to join the cross-functional global drug development teams. A highly motivated individual, the Senior Principal Scientist will focus on strategic development and implementation of novel data science and predictive analytics methodologies to support clinical drug development. We are seeking a Subject Matter Expert who will apply innovative quantitative tools, e.g., AI/ML based analytics, multivariate statistical and empirical modeling, to complement the Pharmacokinetic/Pharmacodynamic (PK/PD) modeling approaches to ensure development of safe & effective therapies. In this vital role, you will be responsible for developing and executing an integrated predictive analytics strategy to expand the role of pharmacometric analysis by incorporating novel data, including medical imaging and electronic health records. Typical role includes working on a wide range of activities such as working with complex structured and unstructured datasets, developing/recommending novel machine learning tools, data visualizations, automation of analytics workflows, disease progression models, mechanistic and empirical PK/PD models, clinical trial simulations, literature meta-analysis using quantitative approaches and statistical modeling of historical and preclinical data. The candidate is expected to be able to integrate modeling and simulation results into cross-functional interactions, regulatory filings, and their application to dose selection, study design, risk/benefit, and advising drug development decisions in close collaboration with other R&D partners. Other key responsibilities may include: - Design and implement AI/ML driven analytics to help with clinical drug development plans and provide expertise to project teams including plan, design, execution and oversight of using it for multiple programs in Amgen portfolio.
- Expand the pharmacometric modeling to include information from novel data sources (e.g., medical images, electronic health records) and support quantitative drug development.
- Adapt data science algorithms (supervised and unsupervised learning, decision trees, neural networks, AI based image processing and feature extraction, Bayesian learning, etc.) for modeling clinical trial data to support drug development.
- Responsible for planning and implementation of analyses to integrate knowledge of pharmacokinetics, pharmacodynamics, patient characteristics and disease states to optimize doses, dosage regimens and study designs.
- Influence external environment through methods such as publication and presentations.
- Responsible for collaborating with partners (e.g., clinical pharmacologists, clinical assay group, statistics) to ensure appropriate support for programs and studies.
- Provide thought leadership, guidance and advice in own field, and develop innovative and creative output based on interpretation and analysis.
- May mentor scientific staff. What we expect of you: The dynamic professional we seek is a leader with these qualifications: Basic Qualifications: Doctorate degree in Applied mathematics, Computer Science, Engineering or related field and 3 years of industry/academic experience Or Master's degree in Applied mathematics, Computer Science, Engineering or related field and 6 years of industry/academic experience Or Bachelor's degree in Applied mathematics, Computer Science, Engineering or related field and 8 years of industry/academic experience Preferred Qualifications:
- PhD in Statistical and Data sciences, Computer Science, Pharmaceutical Sciences, Engineering, or related fields with equivalent professional degrees.
- Candidates with experience in developing methodologies and with knowledge of theoretical foundations of data science methods will be preferred. Academic research experience is welcome and is an advantage.
- Knowledge of machine learning and AI methods and proficiency with scripting and executing data analytics algorithms and models with hands-on experience using a modeling and simulation software (e.g., Python, MATLAB, R, NONMEM, SAS, S-Plus, etc.) is a must.
- Experience in the usage of machine learning/AI tools in life science area(s) and handling life science datasets is preferred. Knowledge of pharmacometric and/or disease modeling using population data will be an advantage.
- Excellent interpersonal, technical and communication skills to work and lead cross-functional teams.
- Demonstrated ability to write modeling results, interpretations (including impact) and conclusions for reports and regulatory documents/interactions.
- Demonstrated record of scientific contributions through peer-reviewed articles and external presentations. What you can expect of us: As we work to develop treatments that take care of others, we also work to care for our teammates' professional and personal growth and well-being.
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