> Markdown version of [/jobs/ext/4525333-data-scientist](https://www.wearedevelopers.com/jobs/ext/4525333-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** PROLIM Global Corporation - **Location:** Austin, TX, United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Audit Trail, Configuration Management, Continuous Integration, Data Validation, Python (Programming Language), Machine Learning, Swagger, Software Engineering, Management of Software Versions, Openapi, Scripting, Fastapi, Git Flow, Integration Tests, Restful APIs, Software Version Control - **Published:** November 2, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-scientist-austin-tx--094e05c2-f87a-473b-b1e2-dd9b667abbb0 ## About the Role Data Science, Software Engineering, Application Programming Interface (API), REST (Representational State Transfer), Python Programming/Scripting Language, Risk Modeling, Risk, Source Code/Configuration Management (SCM), Amazon Web Services (AWS), Loans, Python Fast API Engineer (ML + Risk Modeling) "Strong hands-on experience with Python and Fast API (building production REST services). Experience serving or integrating ML models in production (risk scoring, classification/regression, or similar). Solid engineering practices: unit/integration testing, Git-based workflows, CI/CD, and API documentation (OpenAPI/Swagger). Familiarity with model governance concepts: version control/lineage, monitoring, explainability/reason codes, audit logs. Experience with AWS and/or model execution environments such as SageMaker" "Design and develop REST APIs using Python + Fast API to serve real time model scoring for individual loans/customers and support batch scoring workloads. Integrate APIs with upstream/downstream systems and ensure strong input validation and error handling. Support model hosting & execution for Python-based models and enable flexible deployment patterns Implement model operational capabilities: versioning/lineage, audit trails, reason codes/explainability hooks, and champion challenger support where needed.