Note The job is a remote job and is open to candidates in USA. Simple Technology Solutions is committed to prioritizing its people while delivering exceptional solutions to Federal Government clients. They are seeking a Mid-Level Data Scientist to join their federal data engineering team, where the role involves building AI/ML capabilities and delivering analytical products that support critical government decision-making. Responsibilities 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 Skills US Citizenship is required Bachelor's Degree is required Minimum of 3-5 years' position related experience is required Bachelor's degree or higher in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field 3-5 years of experience in data science, machine learning engineering, or quantitative analytics Proficiency in Python 3.10 (PEP 8) including pandas, NumPy, scikit-learn, and related libraries Hands-on experience with Amazon Bedrock, knowledge bases, vector stores, and RAG pipeline design on AWS Experience with Amazon OpenSearch Services or equivalent vector/search infrastructure Experience with Apache Airflow (MWAA) for DAG-based pipeline orchestration Familiarity with AWS Glue, S3, and Apache Spark for large-scale data processing Experience with SQL and query tools such as Trino, Athena, or Redshift Must be able to work 8am-5pm Eastern Time regardless of home location Active federal public trust suitability determination or ability to obtain one required Experience working with large-scale financial or regulatory datasets is strongly preferred Knowledge of federal AI governance requirements and responsible AI practices in a government setting Experience with agile development, CI/CD pipelines, GitHub, and sprint-based delivery Familiarity with FISMA, NIST 800-53, and Zero Trust principles Benefits Flexibility to help them thrive personally and professionally Special incentives for team members living in qualified HUBZones Company Overview Simple Technology Solutions is a federal-focused digital strategy consultancy. It was founded in 2013, and is headquartered in Washington, District of Columbia, USA, with a workforce of 51-200 employees. Its website is https//www.simpletechnology.io.