Data Scientist

Looking for a Sr. Data Scientist with 5+ years of work experience training and deploying ML models. In addition, you should have at least three years of industry experience developing and deploying ML models for predictive and condition-based maintenance in production.

A few examples of the problems that you will be addressing with Data Science, ML and LLMs:

• Increase Service Engineer/Technical Support Specialist productivity
• Reduce Mean-Time-to-Repair
• Increase First-Time-Fix-Rate
• Increase Mean-Time-Between-Failures
• Reduce unplanned device downtime
• Increase device utilization

You will own the complete end-to-end ML workflow:

• Develop domain expertise and in-depth understanding of different types of medical devices
• Understand and conduct EDA on medical device operational (non-patient) data
• Formulate a business problem into a ML / Data Science problem
• Determine the best ML algorithm and statistical technique for a given problem and dataset
• ETL, cleanse and prepare system data for Machine Learning
• Train, evaluate, deploy, monitor, and manage ML models in production

Requirements

The ideal candidate is an experienced Data Scientist highly skilled in:

• Framing a business problem into a ML / Data Science problem
• Analyzing and preparing complex messy unstructured data for ML
• Training, evaluating, and deploying Failure Prediction and Anomaly Detection models

Minimum (must-have)

• 5+ years' work experience as a Data Scientist developing production-grade ML models
• 3+ years' work experience training and deploying Failure Prediction models in production
• 2+ years' work experience training and deploying Anomaly Detection models in production
• In-depth knowledge of ML algorithms, frameworks, libraries, and related tools
• Excellent exploratory data analysis, data prep and feature engineering skills
• Strong knowledge of statistics and time series data analysis
• 2+ years' work experience using Python and SQL
• Master’s or Ph.D. in Statistics, Computer Science, or another quantitative field