AI/MLOps Data Scientist

Job Family:

Data Science & Analysis

Travel Required:

None

Clearance Required:

Active Secret

What You Will Do:

• Provide data science, artificial intelligence (AI) / machine learning (ML), and analytics support to Department of State clients.
• Identify and address client needs, build client relationships, and drive initiatives forward.
• Focus on a single priority project or drive multiple concurrent projects forward.
• Collaborate with other data scientists and adjacent roles.
• Wrangle, cleanse, and analyze data using Python.
• Develop, evaluate, monitor, and maintain AI/ML predictive models and Natural Language Processing models using Python.
• Develop advanced data visualizations and dashboards using Power BI or Tableau using best practices.
• Perform data science in an Azure environment.
• Leverage data science platforms such as Databricks.
• Work with Lange Language Models.
• Containerize ML models using tools such as Docker and help manage deployments on OpenShift.
• Write technical process flows, diagrams, and model documentation.
• Present products and findings to clients and answer questions about methods and results.
• Stay abreast of the latest advancements in AI/ML methods and technologies and apply them as appropriate.
• Ensure AI/ML deployments adhere to commercial and public sector guidelines, policies and standards, delivering responsible use of AI.
• Provide technical guidance and mentorship to team members.
• Develop trusted relationships with clients at all levels of the organization to obtain a more complete perspective and understanding of our clients’ mission, challenges, and goals to deliver tailored solutions and drive innovation in AI/ML and data science.
• Support business development efforts (e.g., responding to RFPs/RFIs, developing white papers, creating pitch decks and capability briefings, etc.).
• Support internal firm initiatives.
• Continue to develop professionally and expand skills related to data science and consulting.

What You Will Need:

• An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance
• Bachelor’s degree is required
• Minimum FOUR (4) years of relevant professional experience in AI/ML and data science.
• Solid understanding of various supervised and unsupervised ML methods and techniques.
• Proficiency in wrangling data and developing AI/ML models using Python.
• Experience utilizing the Databricks platform to conduct data science.
• Proficiency in developing data visualizations and dashboards using Power BI or Tableau, applying best practices.
• Experience utilizing Large Language Models.
• Understanding of Natural Language Processing.
• Understanding of ML model containerization, such as with Docker.
• Understanding of DevSecOps principles.
• Experience developing data science solutions on cloud platforms (e.g., AWS, Azure, GCP).
• Ability to learn new technical skills.
• Understanding of Agile principles and methodology.
• Ability to operate independently or collaboratively in small teams.
• Strong communication and presentation skills for both technical and non-technical audiences.
• Ability to understand client mission, business processes, and data nuances and adapt data science solutions accordingly.
• Ability to think strategically and drive innovation.
• Ability to operate successfully on remote, hybrid, or on-site projects in the DC metro area.

What Would Be Nice To Have:

• Master's degree
• SIX (6) years of relevant professional experience in AI/ML and data science.
• Proficiency utilizing SQL to query and wrangle data.
• Experience supporting DevSecOps, including integrating security into CI/CD workflows for AI/ML models.
• Experience with Docker for containerizing ML models and managing container lifecycles, including building Docker images.
• Experience with Jenkins for building and automating CI/CD pipelines.
• Experience utilizing GitHub for version control, branching strategies, and CI/CD pipeline integration.
• Experience in OpenShift for deploying and managing containerized applications in a Kubernetes-based environment.
• Experience with deploying AI/ML models on cloud platforms (e.g., AWS, Azure, GCP) and hybrid cloud deployments, including cloud security (e.g., Managed Identities).
• Knowledge of Infrastructure as Code.
• Knowledge of Function Apps.
• Experience working with Virtual Machines and configuring them to be scalable, Azure Blob Storage, working with Desired State Confi