Post Doctoral Fellow - AI / Machine Learning Data Scientist

$76,773 - $87,171/Yr

Amgen - Cambridge, MA

Full-time - Entry Level

Remote - Cambridge, MA

Chemical Manufacturing

About the position

At Amgen, the Post Doctoral Fellow - AI / Machine Learning Data Scientist will play a pivotal role in the Transformative Digital Capabilities (TDC) organization, which is dedicated to advancing computational technologies in biopharmaceutical processes. This position involves developing, maintaining, and deploying machine learning models specifically tailored for biopharmaceutical processes, such as upstream biologics. A strong understanding of process engineering is preferred, as the role requires selecting the appropriate technologies and infrastructure to support these models. The fellow will also facilitate data flow from a centralized data lake to computational models, ensuring that data is effectively utilized in the modeling process. The ideal candidate will possess a robust engineering background combined with expertise in data science, enabling them to tackle complex cross-functional projects. These projects will encompass machine learning, hybrid model development, data analysis, and visualization. The fellow will collaborate closely with subject matter experts (SMEs) and stakeholders, documenting and communicating the technical foundations of the models to ensure they are accessible and beneficial for engineers and scientists alike. This role is not only about technical prowess but also about effective communication and collaboration within diverse teams. Amgen is committed to fostering an environment where unique contributions are valued, and the Post Doctoral Fellow will be expected to leverage their skills and experience to serve patients and contribute to the company's mission of improving lives through innovative biotechnology solutions.

Responsibilities

• Develop, maintain, and deploy machine learning models for biopharmaceutical processes.
• Select underlying technologies and infrastructure for model development.
• Enable data flow from centralized data lake to computational models.
• Collaborate with cross-functional project teams and communicate technical details to engineers and scientists.
• Conduct data analysis and visualization to support project goals.

Requirements

• PhD at time of appointment.
• PhD in an engineering or science field completed by Dec 2024 (preferred).
• Track record of leading data science and machine learning projects.
• 4+ years of coding experience in Python.
• Engineering background with strong machine learning skills.
• Experience in AI and ML algorithms.
• Experience working with experimental data sets and data mining tools such as PyTorch and TensorFlow.
• Understanding of biopharmaceutical processes and related unit operations.
• Experience using Git for version control.
• Familiarity with DevOps and software best practices (version control, continuous integration, test-driven development).
• Experience in Databricks and Spotfire.
• Experience in cloud computing and storage systems such as AWS.
• Excellent communication skills (written and verbal).
• Strong analytical skills with attention to detail.

Nice-to-haves

• Experience in leading cross-functional teams.
• Familiarity with advanced data visualization techniques.
• Knowledge of regulatory requirements in biopharmaceuticals.

Benefits

• Comprehensive employee benefits package including health, dental, and vision coverage.
• Retirement and Savings Plan with generous company contributions.
• Life and disability insurance.
• Flexible spending accounts.
• Discretionary annual bonus program.
• Stock-based long-term incentives.
• Award-winning time-off plans and bi-annual company-wide shutdowns.
• Flexible work models, including remote work arrangements.