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Ai Risk Jobs in Wheat Ridge, CO (NOW HIRING)

Lead the full lifecycle of quantitative model development - from ideation and backtesting to production deployment - across portfolio construction, risk, and factor modeling. * Shape AI-driven ...

AI Data Architect /REMOTE

Denver, CO ยท Remote

$75 - $80/hr

Risk Management: Identify and mitigate risks, including data privacy issues, algorithmic bias, and misuse of AI. * Collaboration: Partner with cross-functional teams to provide technical and ethical ...

Exposure to data and AI governance, model risk management frameworks, or emerging technology compliance EXPERIENCE * Knowledge of external audit workflows and the importance of audit quality ...

... and risk scenarios, generates personalized insights, enforces compliance guardrails, and drafts ... AI Agent Platform & Infrastructure Architect a scalable multi-agent platform with orchestration ...

Strategic execution skills to anticipate legal operational requirements, interpret risk metrics ... Industry AI or legal technology certifications from providers such as Google, AWS, Anthropic/Claude ...

Solution Architect - AI & Data

Denver, CO ยท On-site

$173.20 - $270.60/hr

AI Governance, Risk & Responsible AI * Define and embed AI governance frameworks covering data stewardship, model risk, bias controls, audit trails, and compliance postures. * Support customers in ...

Overview The Sr. Manager, AI Solutions & Delivery for Crocs, Inc. will serve as the operational leader for the project management, solutions analysis, governance, risk, responsible AI, enablement ...

Solution Architect - AI & Data

Denver, CO

$64.75 - $85.50/hr

AI Governance, Risk & Responsible AI * Define and embed AI governance frameworks covering data stewardship, model risk, bias controls, audit trails, and compliance postures. * Support customers in ...

Solution Architect - AI & Data

Denver, CO ยท On-site +1

$64.75 - $85.50/hr

AI Governance, Risk & Responsible AI * Define and embed AI governance frameworks covering data stewardship, model risk, bias controls, audit trails, and compliance postures. * Support customers in ...

Showing results 41-60

Ai Risk information

See Wheat Ridge, CO salary details

$15

$32

$78

How much do ai risk jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for ai risk in Wheat Ridge, CO is $32.24, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $41.11 per hour, depending on experience, location, and employer.

What is the difference between Ai Risk vs Data Scientist?

AspectAi RiskData Scientist
Required CredentialsBackground in AI, risk management, certifications in AI safetyDegree in Computer Science, Statistics, or related fields; certifications in data analysis
Work EnvironmentRisk assessment teams, AI development projects, regulatory settingsData analysis teams, research labs, tech companies
Employer & Industry UsageTech firms, AI safety organizations, regulatory agenciesTech companies, finance, healthcare, research institutions
Common Search & Comparison IntentUnderstanding AI risk roles, career differencesData analysis careers, AI safety roles

Ai Risk professionals focus on identifying and mitigating risks associated with artificial intelligence systems, often working in safety, ethics, and regulatory contexts. Data Scientists analyze large datasets to extract insights, build models, and support decision-making across various industries. While both roles require technical skills, Ai Risk emphasizes safety and ethical considerations, whereas Data Scientists focus on data analysis and modeling.

What cities near Wheat Ridge, CO are hiring for Ai Risk jobs? Cities near Wheat Ridge, CO with the most Ai Risk job openings:

Senior Data Scientist - Scale Risk & Revenue with AI

Thaloz

Denver, CO โ€ข On-site

Other

Posted 4 days ago


Job description

Clearco is a leader in AI and data-driven eCommerce funding, providing non-dilutive capital that helps founders grow without sacrificing equity. We are hiring a Senior Data Scientist to shape the models, experiments, and analytics that drive our risk, underwriting, and revenue decisions.

This hands-on senior role sits at the intersection of Data Science, Machine Learning, and Product. You will partner with Engineering, Product, Risk, and Finance to turn ambiguous problems into production-grade models and measurable outcomes that responsibly scale funding for eCommerce businesses.

Responsibilities
  • Design and execute data science experiments, including causal analysis, A/B tests, and offline evaluation.
  • Develop, evaluate, and iterate on predictive models for credit/risk scoring, revenue forecasting, and policy performance.
  • Own model performance and monitoring: define success metrics, investigate drift, and drive improvements to data quality and feature reliability.
  • Partner with Product Engineering to productionize models and analytics with emphasis on reliability, reproducibility, and maintainability.
  • Perform exploratory data analysis, feature engineering, and robust validation on real-world, messy data.
  • Communicate insights and recommendations clearly to technical and non-technical stakeholders through documentation and presentations.
  • Improve analytical standards, code review practices, and documentation to raise technical quality.
  • Mentor and support team members through pairing, feedback, and sharing best practices.
  • 5+ years of professional experience in data science, applied machine learning, or a related quantitative role.
  • Strong foundations in statistics and experimentation, including hypothesis testing, causal reasoning, and evaluation design.
  • Proven experience building and shipping predictive models (classification, regression, time series) and measuring real-world impact.
  • Strong proficiency in Python and SQL and comfort working with production data workflows.
  • Experience defining success metrics, aligning with stakeholders, and delivering end-to-end outcomes.
  • Strong written communication skills and a pragmatic approach to fast-moving environments.
  • Experience owning model performance, monitoring for drift, and improving feature reliability.
Nice to Have
  • Experience with credit risk, underwriting, fraud/risk signals, or financial forecasting.
  • Experience with modern data tooling and warehouses such as BigQuery or Snowflake and transformation frameworks like dbt.
  • Familiarity with MLOps patterns (model deployment, monitoring, feature stores, orchestration) and cloud environments.
  • Experience working with messy third-party data sources (banking data, eCommerce platforms, marketing signals).
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