Data Scientist

Boston, MA 02212
Full-time

Job Closed

Overview

Job Summary: We are seeking a talented Data Scientists to join our growing Engineering Team. This is a Remote opportunity that will be responsible helping define how our Claims and Underwriting products evolve for the industry. You will do this through user research, rapidly prototyping new features, implementing Machine Learning Systems, and delivery our customers actionable intelligence from large data sets. Top "Must-Have" Skills for this job: • 2-5 years of professional experience as a Data Scientist • Hands-on experience building and productionizing Machine Learning Models (Neural Networks, Random Forest, etc.) • Strong experience in Python scripting and libraries (such as Pandas, NumPy, and PyTorch) • Fluency in SQL and/or PostgreSQL • Experience working with insurance data or building insurance models (nice to have) • Master of Science or PhD (required) Selling Points: • Full Benefits (Medial, Dental, Vision) • 401K • Unlimited PTO, Paid Holidays • Equipment Provided • Remote Opportunity • And much more! Schedule: Monday-Friday, 8-5pm, Remote

Qualifications

Required
  • Master's degree or higher
  • Data Science (2+ years)
  • 2+ years of experience in ANY of the following:
    • Machine Learning Models
    • SQL
    • PostreSQL
Preferred
  • What Python libraries or frameworks have you used before (Pandas, NumPy, Pytorch, Tensorflow, etc.)?
  • Do you have experience working with insurance data or building insurance models? If yes, please explain that experience.
  • What are your minimum salary expectations to consider making a move?
  • What types of Machine learning models have you built (neural networks, random forest, gradient boosted trees, logistic/linear regression)?

Company

Our client is a Software Development company that provides artificial intelligence-driven SaaS solutions exclusively for the insurance industry. Their platform provides bias-free, data-driven insights that helps commercial insurers automate and improve underwriting results, reduce claim costs, and improve operational efficiencies.