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Senior Data Scientist

SOHO Square SolutionsUnited States🇺🇸United StatesPosted 22 Jul 2026

Why This Role Stands Out

Leverage your expertise in advanced analytics and AI to drive product reliability and reduce operational risk in a hybrid environment at SOHO Square Solutions. You'll have the opportunity to implement cutting-edge ML models and LLMs, working collaboratively with cross-functional teams to create impactful solutions. This role is ideal for an experienced data scientist eager to make significant contributions and grow within a reputable technology company.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

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

Skills

Machine Learning

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