Every engineer is empowered to own the full lifecycle of the model, from supporting development, building and testing, to provisioning environments, to monitoring models when they are deployed.

Our Stack

Our Data Science and Actuarial model environment and architecture is containerized, and we are cloud based, running on Azure. We aim to have completely automated processes to build, provision, and deploy our models. Our models will range from parametric, ML, RL, Bayesian, to large simulation models which will each require creative problem solving and a close collaboration with stakeholders across the organization, not limited by a ‘one size fits all’ mindset.

What You’ll Do:

Build on a fully containerized model architecture

Learn provisioning of applications through Infrastructure as Code

Work with and develop a modern CI/CD model pipeline

Structure workflows through a flow tool (Airflow, Luigi, Argo … ), through DAGs

Provision data stores and APIs unique to data science and actuarial models

Develop new forms of data applications and stores useful for DS and Actuarial models

Manage container and model security (Snyk …. )

Who You Are:

Computer Science degree or related field, or equivalent experience

5+ years of experience as a Backend, Data, or Dev-Ops Engineer

Strong knowledge of Python

Strong experience working with relational (SQL) databases

Strong knowledge API security models and authentication in a distributed system

Experience with asynchronous architectures using events, workers, and job queues

Understanding of communication patterns in a distributed system

Experience developing containerized applications using Docker

Understanding of the cloud and experience working with cloud based architectures

Writing automated unit and integration tests

Knowledge of agile development practices using Git and project management tools like Jira

Solid knowledge of Unix / Linux commands and ability to work in terminal, especially server side

Bonus Skills:

Experience with GraphQL, Kubernetes

Experience with NoSQL DBs, columnar DBs, graph DBs

Hands-on knowledge of CI/CD with Github/Azure Actions

Experience with alerting and monitoring tools like Sentry, DataDog

Hands on experience with Azure

Experience working at a start-up or financial services in a lead role

Knowledge of Julia and R