About The Position

Secretariat is seeking a Data Scientist to support both client-facing analytics and the firm’s internal AI initiatives. This role will help design, build, and operationalize data and AI solutions that improve analytical delivery, strengthen internal capability, and support secure, governed use of emerging technologies.

Requirements

  • Bachelor’s or master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related quantitative or technical discipline.
  • 2–4 years of experience in data science, analytics, business intelligence, or a related technical role, with experience delivering solutions in a professional or client-facing environment.
  • Demonstrated experience with Power BI and Databricks, including data modeling, data preparation, analytics, visualization, and production-oriented data workflows.
  • Experience with AWS and AI/LLM infrastructure, including cloud architecture, APIs/integrations, access controls, monitoring, deployment, and production support.

Nice To Haves

  • AWS certification is strongly preferred; relevant certifications include AWS Certified

Responsibilities

  • Develop and support client-facing analytics solutions, including business-intelligence dashboards, data models, large-scale data-processing workflows, and analytical deliverables, in partnership with engagement teams.
  • Build, enhance, and support the firm’s internal AI capabilities, including AI-enabled assistant tools, domain-specific analytical applications, and other large language model-powered solutions.
  • Design, prototype, test, and productionize AI-enabled and agentic workflows that automate repeatable business processes, including intake, triage, research, document review, retrieval, drafting, quality assurance, and escalation.
  • Support cloud-based AI infrastructure, including solution architecture, integrations, access controls, monitoring, security, responsible-AI practices, and production support.
  • Partner with IT and practice teams to translate business and client requirements into scalable data and AI solutions, coordinating access, configuration, deployment, troubleshooting, and handoffs.
  • Document solutions, workflows, and runbooks; monitor adoption and performance; and identify opportunities to strengthen internal AI capabilities, improve scalability, and support secure production use.
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