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Mid-Level Data Scientist

3 weeks ago
United States
Full-time
Mid Level
Data Scientist
Data Science and Analytics
Apache Airflow Apache Spark AWS CI/CD GitHub JIRA Machine Learning NumPy Pandas Python Scikit-learn SQL Trino
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Simple Technology Solutions

Simple Technology Solutions

Simple Technology Solutions specializes in Enterprise Cloud Transformation, providing innovative solutions to enhance organizational efficiency and scalability in the cloud computing sector.

IT Services
51-250
Founded 2013
View All Jobs 3

Description

  • Build and maintain knowledge bases, vector stores, and Retrieval Augmented Generation (RAG) pipelines using Amazon Bedrock and Amazon OpenSearch Services.
  • Support the development, validation, and operationalization of statistical outputs and derived data products.
  • Coordinate with the agency data science team and subject matter expert data scientists to implement Airflow DAGs and AWS Glue jobs for automated updates.
  • Support the transition of data science outputs into production by validating accuracy, completeness, and reporting readiness.
  • Ensure 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.
  • Use AI-assisted development tools for code generation, debugging, and performance tuning while adhering to agency security and federal AI governance requirements.
  • Write Python 3.10 code that conforms to PEP 8 standards and integrate analytical pipelines with ETL metadata infrastructure.
  • Support entity resolution work to ensure consistent identification and linkage of records across high-volume financial datasets.
  • Produce required documentation for analytical models and pipelines, including methodology, data lineage, assumptions, refresh schedules, and IV&V questionnaires.

Requirements

  • US citizenship 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, 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.
  • 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.
  • Must be able to work 8am-5pm Eastern Time regardless of home location.
  • Active federal public trust suitability determination or ability to obtain one is required.

Benefits

  • Flexibility to help employees thrive personally and professionally.
  • HUBZone incentives for team members living in qualified HUBZones.
  • A collaborative culture focused on continuous learning and excellence.
  • Recognition as a “Best Place to Work.”
  • Equal employment opportunity and merit-based employment practices.

Interested in this position?

Apply directly on the company website

Apply Now

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