Senior Data Scientist

Remote
Full-time

Job Closed

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Overview

Our client is searching for a Data Scientist to fill a remote permanent role as soon as possible. We need team members from Junior to Senior that want to help define how our claims and underwriting products evolve for the insurance industry. You'll do this through user research, rapidly prototyping new features, implementing machine learning systems, and delivering our customers actionable intelligence from large data sets.  The Ideal candidate will have a graduate degree in Data Science, Machine Learning or AI and 3 years of working experience Top Skills: 1. 3+ years Python Library(Pandas/NumPy/etc) 2. 2+ years Machine Learning Models (Random Forest/Neural Networks,etc.) 3. 2+ years of SQL/PostgreSQL 4. Experience working with Insurance Data 5. Excellent written and verbal communication   Primary responsibilities for this role include mining and analyzing data pertaining to customers’ business experience to discover critical business insights; synthesize research data, turning data in to actionable insights, and specific model requirements; and quickly deploy out of the box solutions where possible and innovate when necessary. To accomplish this, you will work closely with engineers and production developers to ensure clear, effective communication within the team. You must stay current with advancements in Machine Learning and advocate for the appropriate application of those advancements in our own products.

Qualifications

Required
  • Data Science (3+ years)
  • Machine Learning (3+ years)
  • Python (3+ years)
  • SQL (3+ years)
  • building Machine Learning Models (3+ years)
Preferred
  • Please list all of the following in which you have experience: Pandas, PyTorch, NumPy

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.
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