AI Analyst

Weld County Government

About The Position

Detail-oriented and innovative AI Analyst. This role is pivotal in leveraging artificial intelligence (AI) and machine learning (ML) technologies to analyze complex datasets, develop predictive models, and deliver actionable insights that enhance business operations and decision-making. The ideal candidate will combine technical expertise with strategic thinking to drive AI initiatives across the organization, ensuring solutions are scalable, ethical, and aligned with organizational goals. The ideal candidate will possess a strong foundation in data science and AI technologies, coupled with the ability to think strategically and align technical solutions with organizational objectives. This role requires a balance of technical expertise, analytical rigor, and business acumen to ensure that AI initiatives are scalable, ethical, and compliant with data governance standards. The AI Analyst will collaborate with cross-functional teams, communicate complex concepts to non-technical stakeholders, and champion innovation to position the organization at the forefront of emerging technologies.

Requirements

Bachelor's Degree or 4 years Advance AI development and integration strategies.
Knowledge of Artificial Intelligence & Machine Learning.
Deep understanding of AI/ML concepts, algorithms, and frameworks.
Copilot Studio & Generative AI Platforms.
Knowledge of Microsoft Copilot Studio for building, customizing, and deploying AI-powered copilots and conversational experiences.
Data Science & Analytics.
Expertise in statistical modeling, predictive analytics, and data visualization techniques.
Programming & Development.
Proficiency in languages such as Python, R, or Java for model development and automation.
Cloud & Big Data Platforms.
Familiarity with cloud services (Azure, AWS, GCP) and big data tools.
Data Governance & Compliance.
Understanding of data privacy laws, ethical AI practices, and security standards.
Candidate must pass criminal background check prior to employment start date.
Candidate must pass a Motor Vehicle Record (MVR) evaluation and if hired, will be subject to continuous monthly MVR monitoring and random drug screens throughout employment.
This position is subject to a pre-employment drug screening.
Employment is contingent upon successfully passing the screening in accordance with Weld County policy.
This position is exempt from the minimum wage and overtime requirements of the Fair Labor Standards Act and is therefore ineligible for overtime pay.
As an applicant for this position, you should be aware of Senate Bill 19-085, the Equal Pay for Equal Work Act. The act requires employers to announce the pay range for job openings.

Responsibilities

AI & Machine Learning Model Development - 50%
Design, build, and train predictive and prescriptive models using AI/ML frameworks.
Validate and fine-tune models to ensure accuracy, scalability, and reliability.
Analyze structured and unstructured data to identify patterns, trends, and actionable insights.
Translate analytical findings into clear recommendations for business stakeholders.
Collect, clean, and organize large, complex datasets from multiple sources.
Ensure data quality, integrity, and compliance with governance standards.
Integration & Deployment - 30%
Collaborate with IT and development teams to integrate AI models into enterprise systems.
Monitor and maintain deployed models for performance and continuous improvement.
Work closely with business units to understand operational challenges and identify AI opportunities.
Communicate complex technical concepts to non-technical audiences effectively.
Stay current with emerging AI/ML technologies, tools, and best practices.
Recommend innovative solutions to enhance automation and decision-making processes.
Documentation & Reporting - 10%
Maintain detailed documentation of models, methodologies, and processes.
Prepare reports and dashboards for leadership and stakeholders to support strategic decisions.
Training & Knowledge Sharing - 10%
Provide guidance and training to internal teams on AI tools and techniques.
Promote a culture of data-driven decision-making across the organization.
Conduct periodic audits to ensure models remain aligned with organizational goals.