Machine Learning Risk Management Analyst

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Job Title:  Machine Learning Risk Management Analyst
Location: Utah (Hybrid)
Job-Type:  Full-Time
Salary Range:  $100K – $120K
Position Overview:
We are seeking a Machine Learning Risk Management Analyst to join a growing analytics and risk organization within a highly regulated financial services environment. This role is responsible for independently evaluating and validating statistical and machine learning models used in underwriting, credit decisioning, and other business-critical processes.
The ideal candidate has experience developing predictive models but is interested in a role focused on independent model validation, governance, and risk oversight rather than full-time model development. This individual will partner with internal teams and external stakeholders to ensure models are conceptually sound, appropriately governed, and aligned with regulatory and organizational standards.
This is an excellent opportunity for someone who enjoys combining analytics, risk management, and cross-functional collaboration while presenting findings to technical and executive audiences.
Duties & Responsibilities:

• Independently validate statistical and machine learning models used for underwriting and risk decisioning.
• Evaluate model design, assumptions, methodologies, and performance to ensure conceptual and statistical soundness.
• Maintain model governance documentation, inventories, risk ratings, and validation records.
• Perform ongoing model monitoring and recommend improvements where appropriate.
• Provide independent challenge to model development practices and identify potential model risk.
• Participate in due diligence efforts for new business partnerships and third-party model assessments.
• Support internal and external audit activities related to model governance.
• Collaborate with analytics, data science, credit, and business teams to strengthen model risk management processes.
• Analyze data and contribute to ad hoc reporting and analytical initiatives as needed.
• Present findings and recommendations to senior leadership and cross-functional stakeholders.

Required Experience & Skills:

• Experience developing and/or validating statistical and machine learning models.
• Strong understanding of regression, classification, and predictive modeling techniques.
• Solid foundation in statistical analysis and model performance evaluation.
• Experience with SQL and at least one analytical programming language such as Python, R, or SAS.
• Strong analytical, critical thinking, and problem-solving abilities.
• Excellent written and verbal communication skills, including the ability to present complex technical concepts to executive audiences.
• Bachelor’s degree in Statistics, Mathematics, Data Science, Computer Science, Engineering, Economics, Finance, or a related quantitative field.

Nice to Have Experience:
 

• Graduate degree in a quantitative discipline or equivalent professional experience.
• Experience within banking, financial services, fintech, or another highly regulated industry.
• Familiarity with model governance, model risk management, or model validation frameworks.
• Experience working with third-party vendors or strategic business partners.
• Experience with relational databases and business intelligence tools such as Tableau or Power BI.

Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).

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Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.