Scientist 2, Data Science

Remote Bill rate ***-*** 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 ResponsibilitiesCorrelate post-market data (complaints, service records, field performance) with:Manufacturing processesSupplier quality metricsProduct design changesIdentify emerging failure patterns and translate insights into actionable improvementsLead end-to-end root cause investigations using structured and unstructured dataApply AI/ML models, including LLMs, to enhance analysis, pattern detection, and signal identificationDevelop and deploy advanced analytics solutions, including:Machine learning and predictive modelsStatistical analysis frameworksEmbedding-based similarity searchDesign and implement agentic AI workflows to automate analysis, reasoning, and recommendationsLeverage AI models to augment decision-making and scale analytical capabilities across the organizationPartner with R&D, Quality, Regulatory, Manufacturing, and Field Service teams to translate insights into impactDeliver proactive insights to support risk detection, product improvement, and operational excellence Required Qualifications7-10+ years of experience in data science, advanced analytics, or related fieldMaster's degree in Data Science, Statistics, or a related disciplineExperience in medical device or regulated manufacturing environmentsStrong understanding of FDA regulations and Quality Management Systems (QMS) Technical Skills Advanced Analytics & Statistical ExpertiseStrong foundation in statistical modeling and hypothesis testingExpertise 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 contextExperience with clustering (e.g., K-means), classification, and predictive modeling AI/ML & Agentic AI CapabilitiesDeep expertise in machine learning and advanced analytics techniquesStrong hands-on experience applying AI models (including LLMs) within analytical workflowsExperience with vector embeddings and similarity searchAbility to build and operationalize AI-driven analysis to uncover patterns and insightsExperience designing agentic AI systems for automated reasoning, investigation, and recommendations Domain & Systems KnowledgeStrong experience analyzing manufacturing and operational dataFamiliarity with post-market surveillance data (complaints, service data, vigilance reporting)Hands-on experience with SAP (Tahiti preferred), including underlying data structuresKnowledge of SAP manufacturing and quality modulesUnderstanding of product lifecycle data across design, manufacturing, and field performance Behavioral & Analytical CompetenciesHighly inquisitive, self-driven learner with a strong curiosity to explore complex problemsAbility to independently define analytical strategies and select appropriate methods for different scenariosStrong command of hypothesis testing and statistical reasoning to validate findingsDeep understanding of advanced statistical techniques and experimental designCritical thinker who can connect patterns across disparate datasets and challenge assumptionsProactive mindset focused on continuous learning, innovation, and improvementAbility to translate complex analysis into clear, actionable insights for business stakeholders Remote Bill rate ***-*** 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 ResponsibilitiesCorrelate post-market data (complaints, service records, field performance) with:Manufacturing processesSupplier quality metricsProduct design changesIdentify emerging failure patterns and translate insights into actionable improvementsLead end-to-end root cause investigations using structured and unstructured dataApply AI/ML models, including LLMs, to enhance analysis, pattern detection, and signal identificationDevelop and deploy advanced analytics solutions, including:Machine learning and predictive modelsStatistical analysis frameworksEmbedding-based similarity searchDesign and implement agentic AI workflows to automate analysis, reasoning, and recommendationsLeverage AI models to augment decision-making and scale analytical capabilities across the organizationPartner with R&D, Quality, Regulatory, Manufacturing, and Field Service teams to translate insights into impactDeliver proactive insights to support risk detection, product improvement, and operational excellence Required Qualifications7-10+ years of experience in data science, advanced analytics, or related fieldMaster's degree in Data Science, Statistics, or a related disciplineExperience in medical device or regulated manufacturing environmentsStrong understanding of FDA regulations and Quality Management Systems (QMS) Technical Skills Advanced Analytics & Statistical ExpertiseStrong foundation in statistical modeling and hypothesis testingExpertise 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 contextExperience with clustering (e.g., K-means), classification, and predictive modeling AI/ML & Agentic AI CapabilitiesDeep expertise in machine learning and advanced analytics techniquesStrong hands-on experience applying AI models (including LLMs) within analytical workflowsExperience with vector embeddings and similarity searchAbility to build and operationalize AI-driven analysis to uncover patterns and insightsExperience designing agentic AI systems for automated reasoning, investigation, and recommendations Domain & Systems KnowledgeStrong experience analyzing manufacturing and operational dataFamiliarity with post-market surveillance data (complaints, service data, vigilance reporting)Hands-on experience with SAP (Tahiti preferred), including underlying data structuresKnowledge of SAP manufacturing and quality modulesUnderstanding of product lifecycle data across design, manufacturing, and field performance Behavioral & Analytical CompetenciesHighly inquisitive, self-driven learner with a strong curiosity to explore complex problemsAbility to independently define analytical strategies and select appropriate methods for different scenariosStrong command of hypothesis testing and statistical reasoning to validate findingsDeep understanding of advanced statistical techniques and experimental designCritical thinker who can connect patterns across disparate datasets and challenge assumptionsProactive mindset focused on continuous learning, innovation, and improvementAbility to translate complex analysis into clear, actionable insights for business stakeholders ['Anthropic Claude AI', 'Applied Machine Learning', 'Applied Statistics', 'Databricks Mosaic AI', 'Databricks SQL', 'Vector Embeddings'] Shift: ['Anthropic Claude AI', 'Applied Machine Learning', 'Applied Statistics', 'Databricks Mosaic AI', 'Databricks SQL', 'Vector Embeddings']