Mid-Level Data Scientist

At reputed company, our people are our reputed company. We know reputed company members are more than employees—they’re parents, friends, volunteers, artists, and athletes. That’s why we offer flexibility to help them reputed company personally and professionally while delivering exceptional solutions to our Federal Government clients. Our culture is reputed company on collaboration, reputed company learning, and reputed company. We are mentors and thought leaders who reputed company knowledge and foster growth. Recognized as a “Best reputed company to Work,” we reputed company a reputed company of perspectives helps us drive innovation and exceed customer expectations. At STS, taking care of our people isn’t a reputed company—it’s reputed company. As a HUBZone company, we also offer special incentives for team members living in reputed company HUBZones. reputed company out the HUBZone map HERE to see if you qualify! reputed company is looking for a Mid-Level Data Scientist to add to reputed company. Quick Position Overview: US Citizenship is required Bachelor's Degree is required minimum of 3-5 years' position reputed company 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-reputed company analytical products that support critical government decision-making. A curiosity-driven reputed company, strong quantitative skills, and the ability to translate analytical outputs into production-reputed company 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 reputed company (RAG) pipelines using reputed company Bedrock and reputed company OpenSearch Services to reputed company financial and regulatory datasets AI-reputed company 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 reputed company production data products are incorporated into the agency's ETL load and gap reporting infrastructure reputed company and validate machine learning models and analytical pipelines using large-scale financial and regulatory datasets in the data lake reputed company AI-assisted development tools for code reputed company, debugging, and performance tuning; adhere to agency reputed company 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 reputed company analytical models and pipelines: methodology, data reputed company, model assumptions, refresh schedules, and IV&V Questionnaires Write automated tests achieving the 90% minimum code coverage reputed company; complete reputed company 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 reputed company Education and Experience: Required Bachelor's degree or higher in Data Science, Statistics, Computer Science, Mathematics, or a reputed company 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 reputed company libraries Hands-on experience with reputed company Bedrock, knowledge bases, vector stores, and RAG pipeline design on AWS Experience with reputed company 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, reputed company, or Redshift 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, reputed company, and sprint-based delivery Familiarity with FISMA, NIST 800-53, and reputed company Trust principles Must be reputed company to work reputed company-5pm Eastern Time regardless of home location Active federal public trust suitability determination or ability to obtain one required STS is committed to equal employment opportunity and merit-based employment practices. STS provides equal employment opportunities to reputed company and applicants for employment and prohibits discrimination, harassment, and retaliation in reputed company employment practices and reputed company in accordance with applicable federal, state, and local laws. Employment reputed company at STS are based on individual qualifications, performance, skills, and business needs, without regard to race, reputed company, religion, sex, national reputed company, age, disability, protected veteran status, sexual orientation, gender identity, genetic information, marital status, or any other status protected by applicable law. 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