Software Engineer- Full Stack, Cyber Risk Analytics - San Mateo, CA

About Guidewire Cyence Risk Analytics

Guidewire Software (NYSE: GWRE) is a leading provider of software solutions to the global property-casualty (P&C) insurance industry, with over 300 customers, on six continents. Guidewire’s Cyence Risk Analytics helps insurers and other financial institutions to model new and evolving risks such as cyber. By combining internet-scale data listening, adaptive machine learning, and insurance risk modeling, Cyence insights that help P&C customers face new risks, take advantage of new opportunities, and develop new products. To learn more about Cyence, visit


Full-Stack Software Engineer



  • Develop interactive enterprise web applications, with an emphasis on data analytics and visualization
  • Actively participate in a fast-paced team-based Agile environment, working with product managers, user-experience designers, software testers and other engineers



  • Bachelor’s or Master’s Degree in Computer Science or equivalent
  • 4 to 7 years’ experience in full stack engineering or similar equivalent role
  • Excellent programming skills coupled with an understanding of object-oriented design patterns
  • Demonstrated experience developing browser-based interactive web applications, both server-side and client-side
  • Proficiency with JavaScript and strong familiarity with best-practices, design patterns, debugging, code optimization, etc.
  • Strong background in Python  
  • Solid knowledge of databases and SQL
  • Familiarity with Node.js and associated frameworks such as Express.js
  • Familiarity with JavaScript MVC frameworks such as AngularJS or React
  • Familiarity with HTML5 and CSS3, including frameworks such as Bootstrap or Material
  • Experience with version control systems such as Git
  • Curiosity to learn new technologies and go outside your comfort zone
  • Ability to work independently in a fast-paced team environment


  • Experience with data visualization libraries such as D3.js
  • Experience with data analysis tools such as R
  • Experience with Amazon AWS services such as S3, SQS, Redshift


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