• Verisk Analytics
  • Jersey City , NJ
  • Information Technology
  • Full-Time
  • 10 Bayside Terrace

Company Description With a history of impressive growth, an innovative culture, and offering industry-leading solutions, Verisk Analytics is an amazing place to work and make a difference. In 2018, Forbes magazine named Verisk to its World's Best Employers list and, in 2017, to its World's Most Innovative Companies list for the third consecutive year. We also earned the Great Place to Work Certification for the third consecutive year in recognition of our outstanding workplace culture. Verisk is a leading data analytics provider serving customers in insurance, energy and specialized markets, and financial services. Using advanced technologies to collect and analyze billions of records, Verisk draws on unique data assets and deep domain expertise to provide first-to-market innovations integrated into customer workflows. We've been delivering predictive analytics and decision support solutions to our customers for nearly 50 years, helping them protect people, property, and financial assets. At Verisk, you'll be part of an organization that's committed to serving the long-term interests of our stakeholders, including the communities where we operate. At Verisk, you can build an exciting career with meaningful work; create a positive and lasting impact on the business; and find the support, coaching, and training you need to advance your career. Our culture of innovation means your ideas on how to improve our business will be heard. As key contributors to our success, our team members enjoy working in a business-casual, collaborative environment that offers state-of-the-art resources, advanced technologies, and an excellent benefits package. Job Description Position Overview: The DevOps engineer position is embedded within an Analytics Center of Excellence supplying analytics (Machine learning and BI) for a suite of SaaS products. The engineer will guide a team of Data Scientists in the adoption of DevOps and CI/CD principles to improve all the steps of application and AI algorithm development, from integration through deployment with the end goal of reducing development cycles, increasing deployment frequency and dependability, and alignment with business objectives. There will be a special focus on the development of highly available, scalable analytics microservices on AWS infrastructure. Principal Responsibilities and Essential Duties: Train a team of Data Scientists to adopt DataOps (DevOps) principles Train and support data analytics professionals in implementing CI/CD workflows Assists data scientists in the adoption of software development best practices Coach data professionals to write production-grade software Build and maintain automated testing and validation pipelines Take data products from R&D to production Deploy and maintain custom machine learning models as highly available, scalable microservices Integrate analytics development into SaaS products and package them into standalone products for an external market Advise on system architecture and cloud management Serve as liaison to an enterprise cloud Architecture/ Operations team and with IT Help guide our strategy for the selection and development of a host of storage, compute, and analytics tools Provision and maintain development and production architecture stacks Qualifications BS degree in Computer Science or related field or equivalent work experience 4+ years of production engineering related experience Solid knowledge of DevOps principles and experience with CI/CD tools: Source Control software such as Git CI tools such as CodeDeploy, Jenkins / Bamboo or equivalent Build automation tools such as Maven / Ant or equivalent Configuration management software such as Puppet/Chef/CF Engine or equivalent. Experience with Artifact repository tools such as Artifactory Ability to build out, deploy, and maintain analytics applications in Pre-Production and Production environments on AWS Experience with AWS services such as CloudFormation, EC2, S3, Lambda, API Gateway, RDS, CodePipeline, etc. Strong knowledge of application architecture concepts Experience in monitoring application performance and server health with tools such as New Relic, Nagios, CloudWatch and Splunk. Familiarity with computer networking concepts Experience working with Data Scientists and other data professionals or data products preferred Strong scripting experience with Python and shell scripting preferred Experience with distributed computing tools such as Hadoop, EMR and Spark preferred AWS certification is a plusSalary Range: NAMinimum Qualification5 - 7 years
Associated topics: .net, application architect, application developer, architect, design pattern, devops, matlab, maven, project architect, software engineer lead

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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