ABOUT AMGEN 

Job Description 

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.  

ABOUT THE ROLE  

Role Description:  

The Data Scientist is responsible for developing and implementing AI-driven solutions to enhance cybersecurity measures within the organization. This role involves leveraging data science techniques to analyze security data, detect threats, and enhance security processes with generative AI and other analytic capabilities. The Data Scientist will work closely with cybersecurity teams to identify data-driven automation opportunities which strengthen the organization’s security posture.   

Roles & Responsibilities:   

• Develop analytics, machine learning models, and agentic AI solutions to address security risks, improve detection capabilities, and enhance the organization’s cybersecurity posture. 

• Design, build, and evaluate AI agents and multi-agent workflows that support cybersecurity use cases such as automated threat detection, alert triage, incident investigation, vulnerability analysis, and response orchestration. 

• Apply generative AI, large language models, retrieval-augmented generation, and agent-based architectures to automate security analysis, summarize findings, recommend actions, and support human-in-the-loop decision-making. 

• Collaborate with Data Engineers to translate security-focused algorithms, AI agents, and automation workflows into scalable, production-ready solutions. 

• Design and implement security-focused analytics pipelines leveraging MLOps practices, generative AI, and agent-based architectures (e.g, autonomous agents for threat detection and response).  

• Collaborate with cybersecurity teams to identify opportunities where AI agents can reduce manual effort, accelerate investigation timelines, and improve consistency in security operations. 

• Contribute to data engineering efforts to refine data infrastructure and ensure scalable, efficient security analytics.  

• 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.  

Functional Skills:  

Basic Qualifications:  

• Master’s degree OR Bachelor’s degree and 5 to 9 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) 

Preferred Qualifications:  

• Experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)  

• Experience applying generative AI and agent-based systems to cybersecurity use cases (e.g., automated threat detection, response orchestration, and security analysis)  

• Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets  

• Strong foundation in machine learning algorithms and techniques  

• Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification  

Good-to-Have Skills:  

• Proficiency in Python and relevant ML, AI, and agent development libraries such as TensorFlow, PyTorch, Scikit-learn, LangChain, LlamaIndex, Semantic Kernel, AutoGen, or similar frameworks. 

• Experience with generative AI platforms, LLM APIs, vector databases, embedding models, retrieval pipelines, and prompt evaluation techniques. 

• Experience with data engineering and pipeline development  

• Experience in analyzing time-series data for forecasting and trend analysis  

• Experience with AWS, Azure, or Google Cloud  

• Experience with Databricks platform for data analytics and MLOps  

• Experience working in Product teams environment  

• Experience working in an Agile environment  

Professional Certifications :  

• Any AWS Developer certification (preferred)  

• Any Python and ML certification (preferred)  

• Any SAFe Agile certification (preferred)  

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 troubleshooting skills.  

• Strong verbal and written communication skills  

• Ability to work effectively with global, virtual teams  

• High degree of initiative and self-motivation.  

• Ability to manage multiple priorities successfully.  

• Team-oriented, with a focus on achieving team goals