Role Description:
In this vital role you will leverage advanced analytics, AI, and GenAI capabilities to unlock insights and drive innovation in Amgens finance landscape. You will be an integral member of a dynamic product team that builds and deploys financial planning and AI-driven solutions, harnessing Finance data from Amgens enterprise data lake. If you are a passionate data scientist with a track record of applying AI/ML to real-world business problemsand you want to influence how a leading biotech company uses its datathis is the role for you!
Roles & Responsibilities:
- Collaborate with Finance stakeholders to identify and prioritize high-value AI/ML and GenAI use cases that deliver measurable business value.
- Develop, train, validate, and deploy machine learning, natural language processing (NLP), and GenAI models to solve finance-specific problems such as forecasting, scenario modeling, anomaly detection, and intelligent automation.
- Partner with data engineering teams to access and prepare curated datasets from Amgens enterprise data lake for advanced analytics.
- Apply prompt engineering and fine-tuning techniques to adapt large language models (LLMs).
- Create and maintain AI/ML solution documentation, including methodology, model interpretability, and compliance considerations in a regulated environment.
- Establish and promote best practices for responsible AI, model governance, and ethical use of AI in Finance.
- Stay current with industry trends and emerging technologies in AI, GenAI, and advanced analytics, and assess their applicability to Amgen Finance.
Basic Qualifications and Experience:
- Masters/ Bachelors degree and 8 to 14 years of Computer Science, IT or related field experience.
Functional Skills:
Must-Have Skills:
- Strong proficiency in Python for data analysis, ML, and AI development (Pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
- Hands-on experience with large language models (LLMs), prompt engineering, and fine-tuning using frameworks like Hugging Face Transformers.
- Expertise building machine learning workflows for forecasting and statistical modeling.
- Experience with GenAI APIs (e.g., OpenAI, Azure OpenAI, Anthropic Claude) and vector databases (e.g., Pinecone, FAISS) for retrieval-augmented generation (RAG).
- Proficiency in Python, PySpark, and Scala for data processing, with hands-on experience in using Databricks for building ETL pipelines and handling big data processing
- Experience with data warehousing platforms such as Amazon Redshift, or Snowflake.
- Proven ability to translate business problems into technical solutions, with measurable outcomes.
Good-to-Have Skills:
- Experience applying AI to Finance-related domains (forecasting, planning).
- Familiarity with visualization tools (Tableau, Power BI) for presenting AI-driven insights.
- Understanding of DevOps tools and practices for continuous integration/continuous deployment (CI/CD) of ML models.
- Familiarity with Enterprise Performance Management (EPM) solutions like Anaplan, Hyperion, SAP Analytics Cloud Planning
Professional Certifications:
- AWS Certified Machine Learning Specialty (preferred)
- Databricks Certified Machine Learning Professional (preferred)
Soft Skills:
- Excellent critical-thinking and problem-solving skills
- Strong collaboration and communication abilities, with the ability to explain AI concepts to non-technical audiences
- Self-motivated with a high degree of initiative
- Ability to manage multiple priorities in a fast-paced, dynamic environment
- Comfortable working in an Agile environment and contributing to continuous delivery cycles
Shift Information:
This position requires you to work a later shift and may be assigned a second or third shift schedule. Candidates must be willing and able to work during evening or night shifts, as required based on business requirements.