RCI-BDX-3470 Senior Data Scientist (Machine Learning/Statistics/Anthropic Claude AI/Databricks/Vector Embeddings) (Medical Device)

Must Have • Anthropic Claude AI • Applied Machine Learning • Applied Statistics • Databricks Mosaic AI • Databricks SQL • Vector Embeddings Nice To Have • Power BI Role Overview • We are seeking a highly experienced Senior Data Scientist to drive advanced analytics across post-market surveillance, manufacturing, supplier quality, and product design. • This role will focus on identifying systemic failure patterns, enabling robust root cause analysis, and delivering proactive, AI-driven recommendations to improve product reliability and reduce operational risk. Key Responsibilities Correlate post-market data (complaints, service records, field performance) with: • Manufacturing processes • Supplier quality metrics • Product design changes • Identify emerging failure patterns and translate insights into actionable improvements • Lead end-to-end root cause investigations using structured and unstructured data • Apply AI/ML models, including LLMs, to enhance analysis, pattern detection, and signal identification • Develop and deploy advanced analytics solutions, including: • Machine learning and predictive models • Statistical analysis frameworks • Embedding-based similarity search • Design and implement agentic AI workflows to automate analysis, reasoning, and recommendations • Leverage AI models to augment decision-making and scale analytical capabilities across the organization • Partner with R&D, Quality, Regulatory, Manufacturing, and Field Service teams to translate insights into impact • Deliver proactive insights to support risk detection, product improvement, and operational excellence Required Qualifications • 7–10+ years of experience in data science, advanced analytics, or related field • Master’s degree in Data Science, Statistics, or a related discipline • Experience in medical device or regulated manufacturing environments • Strong understanding of FDA regulations and Quality Management Systems (QMS) Technical Skills Advanced Analytics & Statistical Expertise • Strong foundation in statistical modeling and hypothesis testing • Expertise in experimental design and statistical inference (e.g., t-tests, significance testing, confidence intervals) • Ability to select and apply appropriate statistical techniques based on problem context • Experience with clustering (e.g., K-means), classification, and predictive modeling AI/ML & Agentic AI Capabilities • Deep expertise in machine learning and advanced analytics techniques • Strong hands-on experience applying AI models (including LLMs) within analytical workflows • Experience with vector embeddings and similarity search • Ability to build and operationalize AI-driven analysis to uncover patterns and insights • Experience designing agentic AI systems for automated reasoning, investigation, and recommendations Domain & Systems Knowledge • Strong experience analyzing manufacturing and operational data • Familiarity with post-market surveillance data (complaints, service data, vigilance reporting) • Hands-on experience with SAP (Tahiti preferred), including underlying data structures • Knowledge of SAP manufacturing and quality modules • Understanding of product lifecycle data across design, manufacturing, and field performance Behavioral & Analytical Competencies • Highly inquisitive, self-driven learner with a strong curiosity to explore complex problems • Ability to independently define analytical strategies and select appropriate methods for different scenarios • Strong command of hypothesis testing and statistical reasoning to validate findings • Deep understanding of advanced statistical techniques and experimental design • Critical thinker who can connect patterns across disparate datasets and challenge assumptions • Proactive mindset focused on continuous learning, innovation, and improvement • Ability to translate complex analysis into clear, actionable insights for business stakeholders