[Remote] Principal Data Scientist - AI Context Architect (Semantic & Context Engineering)

Note: The job is a remote job and is open to candidates in USA. Amgen is a leading biotechnology company focused on serving patients with serious illnesses. The Principal Data Scientist will act as a senior individual-contributor authority on semantic modeling and AI-first data science, responsible for defining semantic representations and ensuring model reliability through context engineering.

Responsibilities

• Define enterprise-grade semantic representations for healthcare/life-sciences concepts and specify how relationships and interactions are represented for AI consumption
• Create and maintain semantic schemas / ontologies / knowledge-graph models that describe entities, attributes, constraints, and linkages—optimized for both analytics and AI reasoning
• Establish context engineering standards: how data is shaped into prompts, tools, memory, retrieval indices, and structured outputs so models behave consistently across use cases
• Lead feature engineering strategy tied directly to model performance, including feature definition, transformations, leakage prevention, stability monitoring, and explainability
• Perform exploratory data analysis on complex, high-dimensional datasets to identify predictive signals and context variables that improve model robustness and generalization
• Build and evaluate context-aware ML/GenAI solutions, integrating semantic layers with retrieval, tools, and structured outputs
• Apply reinforcement learning concepts (reward modeling, policy optimization intuition, offline evaluation, exploration/exploitation framing) to improve decisioning, ranking, orchestration, and system behavior—without overfitting to short-term metrics
• Prototype and benchmark algorithms and approaches (classical ML, deep learning, LLM-based reasoning) and advise on scalability and production readiness
• Architect and implement retrieval and memory patterns (RAG, vector stores, knowledge graphs, session memory)
• Define data quality and semantic quality gates (entity completeness, relationship validity, taxonomy drift, grounding coverage) that impact downstream model reliability
• Translate domain needs into semantic + AI roadmaps, aligning stakeholders on definitions, metrics, and tradeoffs
• Act as a principal-level mentor and technical leader: establish standards, review semantic designs, and guide teams on best practices for context engineering and feature excellence

Skills

• Doctorate degree and 2 years of Data Science, Computer Science, Statistics, Applied Math, or related experience
• Master's degree and 4 years of Data Science, Computer Science, Statistics, Applied Math, or related experience
• Bachelor's degree and 6 years of Data Science, Computer Science, Statistics, Applied Math, or related experience
• Associate's degree and 10 years of Data Science, Computer Science, Statistics, Applied Math, or related experience
• High school diploma / GED and 12 years of Data Science, Computer Science, Statistics, Applied Math, or related experience
• 10–12+ years applying data science in enterprise environments with demonstrated principal-level influence (or equivalent depth of expertise)
• Deep expertise in semantic modeling: ontologies, taxonomies, entity resolution, knowledge graphs, metadata and data contracts—built for operational use
• Strong understanding of machine learning fundamentals and performance drivers, especially feature engineering and evaluation rigor
• Practical experience implementing RAG / retrieval / vector search / knowledge graph solutions with clear governance patterns
• Working knowledge of reinforcement learning concepts and how they apply to ranking, orchestration, personalization, or decision systems (even if not “pure RL” production)
• Proficiency in Python (and strong comfort with modern data/ML stacks); ability to collaborate effectively with engineering teams on production concerns
• Exceptional stakeholder management: can drive alignment on, relationships, and metrics, and communicate tradeoffs clearly

Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible.

Company Overview

• Amgen is a biotechnology company that develops and manufactures human therapeutics for various illnesses and diseases. It was founded in 1980, and is headquartered in Thousand Oaks, California, USA, with a workforce of 10001+ employees. Its website is http://www.amgen.com.

Company H1B Sponsorship

• Amgen has a track record of offering H1B sponsorships, with 429 in 2025, 485 in 2024, 485 in 2023, 540 in 2022, 460 in 2021, 444 in 2020. Please note that this does not guarantee sponsorship for this specific role.

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