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Scientist 2, Data Science

Saviance Technologies

San Diego, CA

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JOB DETAILS
SKILLS
Analysis Skills, Artificial Intelligence (AI), Data Science, Data Structures, Experiment Design, FDA Requirements, Machine Learning, Manufacturing, Manufacturing Analysis, Manufacturing Operations, Manufacturing Requirements, Manufacturing/Industrial Processes, Medical Equipment, On Site Support, Operational Improvement, Predictive Modeling, Process Improvement, Product Design, Product Lifecycle, Quality Management, Quality Metrics, Reliability Engineering, Research & Development (R&D), Risk, Risk Management, Root Cause Analysis, SAP, Statistical Modeling, Statistics, Structured Data, Surveillance, Unstructured Data, Workflow Analysis
LOCATION
San Diego, CA
POSTED
1 day ago

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 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

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 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

['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']

About the Company

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Saviance Technologies

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