Job Opportunities API

At Simple Technology Solutions, our people are our priority. We know our team members are more than employees—they’re parents, friends, volunteers, artists, and athletes. That’s why we offer flexibility to help them thrive personally and professionally while delivering exceptional solutions to our Federal Government clients. Our culture is built on collaboration, continuous learning, and excellence. We are mentors and thought leaders who share knowledge and foster growth. Recognized as a “Best Place to Work,” we believe a range of perspectives helps us drive innovation and exceed customer expectations. At STS, taking care of our people isn’t a perk—it’s the standard. As a HUBZone company, we also offer special incentives for team members living in qualified HUBZones. Check out the HUBZone map  HERE to see if you qualify! Simple Technology Solutions is looking for a Mid-Level Data Scientist to add to our team. Quick Position Overview: US Citizenship is required Bachelor's Degree is required minimum of 3-5 years' position related experience is required The Role:   STS is looking for a Mid-Level Data Scientist to join a federal data engineering team. You will work on a modern AWS-based federal data platform, building AI/ML  capabilities  and delivering production-ready analytical products that support critical government decision-making. A curiosity-driven mindset, strong quantitative skills, and the ability to translate analytical outputs into production-ready data products conforming to agency standards are prerequisites for this position.   This position is contingent upon contract award.   The Mid-Level Data Scientist at STS will:   Build and  maintain  knowledge bases, vector stores, and Retrieval Augmented Generation (RAG) pipelines using Amazon Bedrock and Amazon OpenSearch Services to make financial and regulatory datasets AI-ready for advanced analytics and machine learning consumption   Support the development, validation, and operationalization of statistical outputs and derived data products; coordinate with the agency data science team and SME data scientists to implement Airflow DAGs and AWS Glue jobs that ensure automated, recurring updates   Support transition of data science outputs into production by  validating  accuracy, completeness, and reporting readiness; ensure all production data products are incorporated into the agency's ETL load and gap reporting infrastructure   Develop and  validate  machine learning models and analytical pipelines using large-scale financial and regulatory datasets in the data lake   Leverage AI-assisted development tools for code generation, debugging, and performance tuning; adhere to agency security standards and applicable federal AI governance requirements   Write Python 3.10 code conforming to PEP 8; integrate analytical pipelines with the agency's ETL metadata infrastructure and produce required load and gap reporting outputs   Support entity resolution work to ensure consistent identification and linkage of records across high-volume financial datasets   Produce required documentation for all analytical models and pipelines:  methodology , data lineage, model assumptions, refresh schedules, and IV&V Questionnaires   Write automated tests achieving the 90%  minimum  code coverage threshold; complete security scans at least once per sprint as part of the Definition of Done per OWASP ASVS Level 2   Participate in 2-week sprint ceremonies, quarterly PI planning, backlog refinement, and agile delivery using JIRA and GitHub     Education and Experience:     Required