Senior Data Scientist

What you will do

In this vital role you will play a key role in a regulatory submission content automation initiative which will modernize and digitize the regulatory submission process, positioning Amgen as a leader in regulatory innovation. The initiative uses state-of-the-art technologies, including Generative AI, Structured Content Management, and integrated data to automate the creation, review, and approval of regulatory content.

• Develop AI/ML/LLM models to serve the regulatory writing group
• Create reusable and effective prompts for LLMs such as OpenAI GPT4, Anthropic Claude etc
• Build evaluation metrics and frameworks for prompt engineering
• Collaborate closely with business key customers to discuss requirements, ensuring alignment between technical capabilities and business objectives, while effectively communicating any technical limitations or constraints.
• Work with data and software engineers on data quality assessment, data cleansing and data ingestion of unstructured documents into vector databases
• Build retrieval algorithms to identify relevant data
• Work in technical teams in development, deployment, and application of models into production tools.
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Share and discuss findings with team members practicing SAFe Agile delivery model.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. We are seeking a highly skilled Senior Data Scientist with a strong MLOps background and experience working with Large Language Models (LLMs) to join our team.

You will play a pivotal role in building and scaling our machine learning models and LLM applications from development to production. Your expertise in both machine learning and operations will be critical in creating efficient and reliable pipelines and applications.

Basic Qualifications:

• Doctorate Degree OR
• Masters degree with 4 to 6 years of experience in Software Engineering, Data Science or Machine Learning Engineering OR
• Bachelors degree with 6 to 8 years of experience in Software Engineering, Data Science or Machine Learning Engineering OR
• Diploma with 10 to 12 years of experience in Software Engineering, Data Science or Machine Learning Engineering
• Experience with building and evaluating LLM applications
• Good foundation in machine learning algorithms and techniques
• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)

Preferred Qualifications:

• Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics in healthcare/biotech
• Knowledge of NLP techniques for text analysis and sentiment analysis
• Experience with AWS, Azure, or Google Cloud

Soft Skills:

• Initiative to explore alternate technology and approaches to solving problems.
• Skilled in breaking down problems, documenting problem statements, and estimating efforts.
• Excellent analytical and solving skills.
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation.
• Ability to handle multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.