Data Scientist

Hi
Hope you are doing well.

Role-Data Scientist
Location-Remote

As a Sr. AI/ML Engineer, and will work with and provide guidance on the organization's implementation of large datasets with specific goals on maintaining and enhancing the quality of data (more than 500M records). Efforts will include implementation and continuous improvement of Machine Learning as a Service (MLaaS), Graph Data Science, and other informed algorithms and AI/ML techniques to improve data usability.

What you ll do:

You'll analyze complex datasets to assess performance or find new patterns

You'll apply machine learning techniques to data sets related to immigration

You'll present results to a diverse audience in presentation or report form

You'll lead architectural design, technical support, and advisement services to ensure identity management system technologies are integrated and meeting the appropriate security requirements

You ll support leadership who engage with senior level executives at a public facing Federal agency and provide subject matter expertise in security architecture and other key domain areas

What you ll need to succeed:

- You have a minimum of ten (10) years of IT experience, focusing on enterprise data architecture and management. - You have at least eight (8) years of experience in Conceptual/Logical/Physical data modeling. - You have experience in identity/entity resolution - You have experience applying graph data science solutions (e.g., leveraging tools like Python, Pandas, Numpy, Sidekick Learn, Neo4j) - You have experience in modeling solutions in AWS that us AI/ML algorithms - You have at least ten (10) years of proven expertise in Relational and Dimensional Data Modeling. - You have experience of cloud architecture, specifically AWS, as it relates to data processing (i.e., EC2, S3, Redshift, etc.). - You are able to define & maintain BI/Data Warehouse methodologies, standards, and industry best practices. - You have experience leading and architecting enterprise-wide initiatives, specifically system integration, data migration, transformation, data warehouse build, data mart build, data lakes implementation / support, as well as O&M etc. for a large enterprise.

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