Salary: $7,991.00 - $11,584.00 Monthly
Location : Denver, CO
Job Type: Full Time
Job Number: SFA-4311-6/2026
Department: Department of Regulatory Agencies
Division: Division of Insurance
Opening Date: 06/09/2026
Closing Date: 6/23/2026 11:59 PM Mountain
FLSA: Determined by Position
Type of Announcement: This position is open only to Colorado state residents.
Primary Physical Work Address: 1560 Broadway, Denver, CO 80202
Department Contact Information:
Salary Note: Although the full salary range for this position is provided, appointments are typically made at or near the range minimum.
How To Apply: Please submit an online application for this position at https://www.governmentjobs.com/careers/colorado. Reach out to the Department Contact to apply using a paper application, including any supplemental questions. Failure to submit a complete and timely application may result in the rejection of your application. Applicants are responsible for ensuring that application materials are received by the appropriate Human Resources office before the closing date and time listed.

Department Information
Hybrid Workplace Arrangement:

Although this position will be designated under the department's hybrid workplace program, it will still be required to report to the department office on a scheduled basis and at the discretion of the supervisor, based on business needs.

This announcement may be used to fill multiple vacancies.

Description of Job
The Colorado Division of Insurance (DOI) regulates the insurance industry in Colorado by helping consumers by answering their questions, investigating their complaints, and helping them understand their insurance. The Division regulates and monitors the insurance companies in Colorado, as well as insurance agents, ensuring all are following the law.

In addition to investigating consumer complaints and reviewing insurer rate and policy form filings, the property and casualty work unit is responsible for implementing Colorado Senate Bill 21-169-Concerning Protecting Consumers from Unfair Discrimination in Insurance Practices, a first-in-the nation effort to address the insurance industry's use of big data and artificial intelligence. SB21-169 prohibits insurers from using external consumer data, algorithms, and predictive models in ways that unfairly discriminate against individuals based on their race, color, national or ethnic origin, religion, sex, sexual orientation, disability, gender identity, or gender expression across a range of insurance practices including underwriting, pricing, claims handling, utilization management, and marketing.

This work unit's responsibilities include engaging with multiple stakeholder communities, drafting regulations and regulatory guidance, reviewing insurers' filings for compliance, monitoring the development of regulatory frameworks related to the governance and quantitative testing of big data and artificial intelligence systems, and collaborating with other state insurance regulators through the National Association of Insurance Commissioners. SB21-169 directs the Division to work with stakeholders before adopting rules on how insurers test their data, algorithms, and predictive models and demonstrate to the Division that their use does not unfairly discriminate against consumers.

Position: SFA 4311

This position develops strategic and programmatic concepts to ensure that insurers' use of big data, algorithms, and predictive models are not unfairly discriminating against protected classes of consumers. This position oversees the development of a leading-edge regulatory framework for the use of big data and artificial intelligence systems in underwriting, pricing, claims handling, and other insurance practices. Specifically, SB21-169 addresses potential unfairly discriminatory outcomes resulting from the use of big data, algorithms, and predictive models in certain insurance practices on the basis of race, color, national or ethnic origin, religion, sex, sexual orientation, disability, gender identity, or gender expression. The result, once the program is successfully implemented, is to ensure equitable treatment by insurers and the financial security it provides to all Coloradans regardless of race, ethnicity, sexual orientation, or other protected characteristics.

Duties include, but are not limited to:

• Developing a regulatory program to regulate insurers' use of big data, algorithms, and predictive models to ensure their use does not result in unfair discrimination;
• Advising, serving as a resource, and coordinating across the division, including working with the actuarial, rates and forms, consumer services, and market conduct teams in such a capacity to implement the program;
• Coordination with other teams to regulate insurers' use of big data, algorithms, and predictive models;
• Analyzing current carrier practices regarding the use of big data, algorithms, and predictive models;
• Performing and/or directing policy research and developing policies, procedures, and regulations in compliance with state law;
• Developing a plan to collect and evaluate carrier-reported data on their use of big data, algorithms, and predictive models and testing for unfairly discriminatory outcomes;
• Directing and conducting stakeholder outreach and engagement with carriers, producers, consumers, consumer advocates, and other interested parties;
• Evaluating carrier compliance and coordinating, as appropriate, enforcement activities;
• Preparing reports and presenting to the General Assembly as part of State Measurement for Accountable, Responsive, and Transparent (SMART) Act hearings;
• Participating in the work of the National Association of Insurance Commissioners (NAIC) and coordinating with other states to address issues as necessary;
• Identifying gaps in enforcement, evaluating the effectiveness of implementation, and making adjustments to the program as data and tools in this area evolve.

Minimum Qualifications, Substitutions, Conditions of Employment & Appeal Rights
MINIMUM QUALIFICATIONS (MQs):

There are two ways to qualify for this position: 1) Experience OR 2) A Combination of Education and Experience

Option 1: Experience

• Nine (9) years of full-time professional* work experience in at least one (1) of the following three (3) areas:
  • Developing or administering risk management and/or governance systems and frameworks for the use of predictive models, machine learning technologies, and big data;
  • Performing quantitative and qualitative analysis, including conducting audits and/or examinations related to data collection and privacy, cybersecurity, algorithmic accountability, risk assessment and remediation, data ethics, and compliance;
  • Developing, evaluating, and validating predictive models, machine learning algorithms, and big data predictive analytics with the ability to assess their accuracy, fairness, and transparency.

Option 2: A Combination of Education AND Experience

• Associate's Degree and Experience: Graduation from an accredited college or university with an associate's degree in public policy, quantitative social science, mathematics, statistics, law, data science, computer science, risk management, actuarial science, or in a field of study related to the work assignment; AND
• Seven (7) years of full-time professional* work experience in at least one (1) of the following three (3) areas:
  • Developing or administering risk management and/or governance systems and frameworks for the use of predictive models, machine learning technologies, and big data;
  • Performing quantitative and qualitative analysis, including conducting audits and/or examinations related to data collection and privacy, cybersecurity, algorithmic accountability, risk assessment and remediation, data ethics, and compliance;
  • Developing, evaluating, and validating predictive models, machine learning algorithms, and big data predictive analytics with the ability to assess their accuracy, fairness, and transparency.

OR

• Bachelor's Degree and Experience: Graduation from an accredited college or university with a bachelor's degree in public policy, quantitative social science, mathematics, statistics, law, data science, computer science, risk management, actuarial science, or in a field of study related to the work assignment; AND
• Five (5) years of full-time professional* work experience in at least one (1) of the following three (3) areas:
  • Developing or administering risk management and/or governance systems and frameworks for the use of predictive models, machine learning technologies, and big data;
  • Performing quantitative and qualitative analysis, including conducting audits and/or examinations related to data collection and privacy, cybersecurity, algorithmic accountability, risk assessment and remediation, data ethics, and/or insurance compliance;
  • Developing, evaluating, and validating predictive models, machine learning algorithms, and big data predictive analytics with the ability to assess their accuracy, fairness, and transparency.

Document this experience in your application IN DETAIL, as your experience will not be inferred or assumed. Part time experience will be prorated.
SUBSTITUTIONS:

• Partial credit toward the degree requirement will be given for completed college/university coursework that did not result in a degree. A master's or doctorate degree from an accredited college or university in a field of study related to the work assignment will substitute for the bachelor's degree requirement.

*Professional work involves exercising discretion, analytical skill, judgment and personal accountability and responsibility for creating, developing, integrating, applying, and sharing an organized body of knowledge that characteristically is: uniquely acquired through an intense education or training regimen at a recognized college or university; equivalent to the curriculum requirements for a bachelor's or higher degree with major study in or pertinent to the specialized field; and continuously studied to explore, extend, and use additional discoveries, interpretations, and application and to improve data, materials, equipment, applications and methods.
Preferred Qualifications:

• Demonstrated professional* experience working in a government agency, in the insurance industry, or in the Colorado Division of Insurance;
• Master's or Doctorate degree in public policy, quantitative social science, mathematics, statistics, law, data science, computer science, risk management, or in a field of study directly related to the work assignment;
• Demonstrated professional* experience working with and knowledge of how predictive models, machine learning algorithms, and big data are utilized within insurance processes such as underwriting, pricing, and claims management, including the identification of potential biases and unintended consequences;
• Demonstrated knowledge of statistical methods and professional* experience in utilizing statistical software and programming languages such as R, Python, or SAS to analyze and interpret complex datasets;
• Demonstrated professional* experience in communicating complex technical issues to non-technical internal and external stakeholders, and engaging effectively with policymakers, industry representatives, and consumer advocates to develop and implement regulatory frameworks;
• Demonstrated professional* experience working in the financial or insurance industries related to implementing policies and practices to address unfair discrimination;
• Demonstrated knowledge, understanding, and professional* experience to ensure equitable access to insurance for all Coloradans regardless of race, ethnicity, sexual orientation, or other protected characteristics;
• Demonstrated professional* experience working in the insurance industry with a focus on enterprise risk management, and/or actuarial or quantitative analysis;
• Demonstrated professional* experience in overseeing policy development related to insurance under both state and federal laws, including drafting regulations;
• Demonstrated professional* experience in promoting the efficient use of policy and regulatory levers to address barriers and create opportunities to advance insurance industry transformation efforts.