Overview: The Data Scientist applies statistical analysis, data processing, and visualization techniques to extract insights from complex datasets, supporting data-driven decision-making. They clean, transform, and analyze structured and unstructured data to identify trends, patterns, and key performance indicators. Using programming languages like Python, R, and SQL, they develop data models, optimize queries, and create dashboards or reports to effectively communicate findings. The Data Scientist collaborates with stakeholders to understand business or mission objectives, ensuring data solutions align with organizational goals. They also maintain data integrity, adhere to security protocols, and implement best practices for data governance and compliance.
Core requirements: - Proficiency in one or more of the following: C++, Python or Java
- Proficiency with Docker (or Podman) and Helm for application packaging and deployment.
- Experience deploying and configuring applications within Kubernetes. (i.e. the ability to define ingress rules for traffic routing, utilize Cert manager for SSL/TLS, and interface with persistent storage (e.g. Longhorn))
- Proficiency with Git based workflows (Bitbucket/GitHub/GitLab)
- Familiarity with the Atlassian Suite (Jira, Confluence, Bitbucket)
- Experience with Agile software development practices including build automation, testing automation, pair programming, and code management.
- Experience supporting configuration management and software release processes.
- Experience with Linux (i.e. RHEL) and comfortable with the command line.
Preferred qualifications:
- Experience managing the full lifecycle of distributed microservices in a production environment
- Experience building scalable RESTful APIs using frameworks such as FastAPI, Flask or Spring Boot.
- Experience implementing asynchronous, event-driven architectures using Kafka or RabbitMQ
- Experience optimizing PostgreSQL for high-volume data and using Redis for distributed caching and state management.
- A deep understanding of cloud-native principals with a focus on building for scalability, high availability, and fault tolerance.
