Senior Data Scientist: AI & LLM for Public Sector

Amivero; United States; On-site; USD 120,000 - 150,000; Full time

Job summary

Amivero, a team of IT professionals delivering digital services to the federal government, seeks a Data Scientist specialized in AI, LLMs, and statistical modeling. You will turn complex data into actionable insights, identify patterns, and support decision making; Azure AI Studio and Databricks experience are highly desirable.

You will work directly with customers and stakeholders, gather requirements, develop models, prompts, and data workflows, and collaborate with data engineers to prepare

Qualifications

• Customer-facing experience with stakeholders.
• Hands-on data scientist or ML engineer experience.
• Experience with LLMs and AI models for data analysis and storytelling.
• Strong understanding of statistical analysis and modeling techniques.
• Proficiency in Python and data science libraries (pandas, NumPy, scikit-learn).
• Experience with large datasets and complex data environments.

Responsibilities

• Collaborate with customers to gather requirements and deliver practical recommendations.
• Develop and evaluate machine learning models and AI solutions.
• Prepare, validate, and structure data for analysis and modeling.
• Build notebooks, experiments, and data science workflows.
• Support deployment and operationalization of models in production environments.

Skills

Data Science

ML Engineering

Python

SQL

LLMs

Statistical Modeling

Data Wrangling

Communication

Customer-facing

Education

Master's Degree

Bachelor's Degree

Tools

Databricks

Azure AI Studio

OpenAI

Hugging Face

MLflow

Spark

Pandas/NumPy

Job description

Amivero, a team of IT professionals delivering digital services to the federal government, seeks a Data Scientist specialized in AI, LLMs, and statistical modeling. You will turn complex data into actionable insights, identify patterns, and support decision making; Azure AI Studio and Databricks experience are highly desirable.

You will work directly with customers and stakeholders, gather requirements, develop models, prompts, and data workflows, and collaborate with data engineers to prepare