The Mosaic Quant Support (MQS) team is mainly responsible for supporting 2 quantitative teams within Investment Science department (ISci), namely the QuantitativeInvestment Group (QIG) and Trading Market Strategies (TMS). This support includes (but is not limited to) all aspects of the users’ technologyinfrastructure and productionizing their analytics, models, and reports. The MQS team is focused on building both Content and Capabilities to empower this ISci quant community at Wellington to provide high quality, data-driven analyses that help inform and guide our Investors, Trading, and Product Management teams. The MQS team is composed primarily of systems engineers and business analysts who work closely with quantitative analysts and investors, data scientists and who interface and coordinate with the broader Information Technology teams to ensure successful solutions delivery.
This position will be primarily responsible for assisting in the delivery of high quality business solutions using the latest in cloud, web, and statistical programming technologies and providing operational support for these ISci systems and users. As part of the MQS technology team, this position will essentially be developing infrastructure as code, providing operational support, and release engineering for the quant team’s systems. This person will also seek to enhance, automate and scale the existing development and operations leveraging the power of AWS, and to participate in all aspects of the software development life cycle. With your Linux (and some Windows) scripting and automation knowledge, you will help improve scalability, performance and monitoring of our production applications. As part of our agile development team, you will work to automate code builds and application testing, and to streamline deployments and releases on AWS. You must have reasonably deep knowledge of AWS service offerings and capabilities (e.g. experience using CloudFormation for multi-environment instantiation in VPCs)
- DevOps role: aide in requirements gathering, rapid prototype systems and services, agile builds and deployment to production, and provide operational support for the production systems and users.
- Member of Mosaic Quant Support team building/supporting applications/infrastructure for Investment Data Science teams.
- Assist in the architecture, buildout, and administration of AWS infrastructure; serve as MQS team’s AWS Subject Matter Expert while collaborating with Mosaic Architects on AWS designs.
- Assist in the designing, scaling, and building of an automated approach across all stage of product development.
- Manage release and deployment cycles for highly available, scalable production infrastructure.
- Integrate with and adhere to Wellington corporate standards and best practices with respect to technology and security,
- Respond to issues when they occur and build automation to prevent problem recurrence
- Partner with Project Managers on estimates, statuses, identifying issues and raising risks
The ideal candidate must have excellent communication skills and a proven ability to put complex systems into production.
- Experience using, managing and monitoring Amazon Web Services is required, in particular with these AWS services (CloudFormation, EC2, S3, CloudWatch).
- 3+ years’ experience with development/deploymenttechnologies and automating a code development/build/release pipeline is desired.
- 5+ years’ experience with and knowledgeable of complete SDLC; must be comfortable with test driven development, continuous integration, and agile development methodologies.
- Experience and familiarity with both Windows and Linux O/S, scripting, and IDEs (strong plus)
- Familiarity with Big Data mining and Quantitative concepts and technologies (a plus)
- Knowledge of REST web services and internet data integration patterns
- Experience monitoring and setting proper alerting thresholds for systems and applications using open source tools
- Prior IT experience at Wellington Management Company (a plus)
- Strong motivation and ability to work in a fast-paced, team-oriented environment that supports a business-critical production and R&D environment. The most critical skill on this team is to be an agile, self-motivated learner.
- Bachelor’s Degree in Computer Science, engineering, math, or related field or equivalent experience.
- Experience in Financial Industry is preferred.