Hiring: Senior Applied Scientist, Amazon Global Data Center Ops Central Insight and Analytics Team Company: Amazon Web Services (AWS) Location: Seattle, WA Job Posted Time: 2026-09-16 18:24:32 Target Skills & Keywords : Fine-tuning, LLM, Machine Learning, NLP, PyTorch, Python, RAG, TensorFlow, scikit-learn About the job Experience: •3+ years of building machine learning models for business application experience •4 years of applied science experience) Required Skills: •Causal inference & root cause analysis:** Build models that decompose fleet-wide metric movements into root causes, distinguishing correlation from causation across operational dimensions (site, service, failure mode, time) •Dose-response modeling:** Develop models that learn the quantitative relationship between intervention intensity and outcome magnitude •Forecasting & projection:** Build time-series models that project metric trajectories under different intervention scenarios, enabling "if we do X, expect Y by date Z" recommendations •Anomaly detection & trend identification:** Develop multi-variate anomaly detection that distinguishes signal from noise in noisy operational data, and identifies emerging patterns before they become crises •Confidence calibration:** Build and maintain calibrated confidence scores for recommendations, ensuring the system knows what it knows and what it doesn't •Outcome attribution:** Design experiments and causal methods to measure the true impact of interventions •Structured reasoning:** Design LLM prompting architectures that reliably transform operational data into executive-quality narrative summaries, decision framings, and recommendation rationales •LLM evaluation:** Build evaluation frameworks that measure LLM output quality (accuracy, actionability, calibration) and detect degradation over time Qualifications: •PhD in Machine Learning, Statistics, Computer Science, Operations Research, or related quantitative field (or Master's + 4 years of applied science experience) •Strong expertise in at least two of: causal inference, time-series forecasting, anomaly detection, NLP/LLMs •Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, statsmodels) •Track record of publications or equivalent internal research contributions •Background in supply chain optimization, capacity planning, or operations research Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!