Applied Data Scientist, Senior (OnSite)

Title: Applied Data Scientist, Senior

Company : U.S. based manufacturer of a life-saving medical devices. 

Location:  Must be local to Chelmsford area for a Hybrid work schedule from Chelmsford based office. NOT REMOTE at this time. 

Description:

Machine Learning and Generative AI Development

• Apply machine learning techniques to derive insights.
• Prepare and structure data for LLM workflows.
• Experiment with emerging AI tools, prototyping new techniques that enhance automation, documentation, and storytelling for decision support.
• Support AI model evaluation, accuracy assessment, and guardrail development for use in regulated environments.
• Frame ambiguous problems, define analytical approaches, and iterate toward transformational solutions.
• Partner with software developers to integrate ML/AI components into internal tools, assistants, and automation solutions.
• Ensure analytic methods and models follow traceability, reproducibility, and documentation expectations suitable for regulated environments.

Data Analytics and Insight Support

• Perform statistical analysis, predictive modeling, and anomaly detection to support engineering and product support decisions.
• Translate complex data into actionable recommendations.
• Develop definitions of KPIs, metrics, and analytical logic.
• Couple analytical models with data visualizations.
• Monitor product failures, service efficiency, operational trends, and customer feedback.
• Partner with IT and data platform teams to access and prepare datasets and data transformations to support dashboards, analytics and AI models.
• Adhere to data privacy, cybersecurity, and internal governance standards when handling service, customer, or field data.

Continuous Improvement and Innovation

• Identify and recommend opportunities for automation, advanced analytics, and AI-driven enhancements to business processes.
• Research and vet 3rd party technology vendors to assess potential partnerships.
• Stay current with emerging AI, ML, and analytics technologies, and evaluate their applicability to current operational

Requirements:

• Minimum education of Bachelor’s Degree in Data Science, Engineering, Computer Science, Applied Mathematics, Statistics, or a related discipline.
• 3+ years of experience in analytics engineering, data analysis, machine learning application development, or similar roles.
• Medical device or regulated industry experience is a MUST.
• Experience working with engineering, product support, or industrial data environments.
• Proficiency developing dashboards, predictive analytics, or AI-driven tools in an engineering, industrial, or operations environment is preferred.
• Experience working with: datasets (Oracle Cloud, Camstar, Salesforce, ServiceMax, etc.); Cloud data platforms (AWS, Azure, etc.); Python for analytics and ML (pandas, numpy, scikit-learn); dashboarding and visualization tools (Power BI, Tableau, or equivalent).
• Experience building predictive models and applying ML techniques to real-world operational data.
• Experience with GenAI tools or modern AI workflows is strongly preferred
• Familiarity with LLM concepts (embeddings, RAG, prompting, semantic search) and demonstrated interest in GenAI experimentation.
  
• Ability to clean, transform, and prepare datasets for analytics and AI workflows.
• Comfort with complex and ambiguous datasets.
• Strong communication and data storytelling abilities.