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Work From Home Model Risk Management Jobs in Oregon

Staff Machine Learning Model Risk Specialist

OR · On-site +1

$98K/yr

This work is essential for Upstart's internal risk management, ensuring that our models help us ... You will apply a risk-based approach across technologies that range from traditional statistical ...

New

We are excited to announce that currently we are looking for a 100% remote (work from home-WFH) ... Recognize operational challenges and suggest recommendations to management, as necessary * Ability ...

WORK FROM HOME

Bend, OR · On-site +1

$300 - $500/wk

We are looking for individuals interested in working from home, remotely, as life insurance sales representatives. We are hiring coachable individuals comfortable with a 100% commission based income ...

WORK FROM HOME

Lake Oswego, OR · On-site +1

$300 - $500/wk

We are looking for individuals interested in working from home, remotely, as life insurance sales representatives. We are hiring coachable individuals comfortable with a 100% commission based income ...

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Work From Home Model Risk Management information

What is a work from home model risk management?

A Work From Home Model Risk Management job involves overseeing and evaluating the risks associated with financial and operational models, such as those used for credit scoring, market forecasting, or regulatory compliance. Professionals in this role ensure that models are accurate, reliable, and compliant with industry standards and regulations. Working remotely, they analyze data, review model documentation, perform validations, and collaborate with other teams to mitigate potential risks. This role typically requires strong analytical skills, knowledge of financial modeling, and familiarity with regulatory guidelines.

What are the key skills and qualifications needed to thrive as a work from home model risk management professional?

To thrive in Work From Home Model Risk Management, you need strong quantitative analysis skills, familiarity with financial modeling, and a background in finance, mathematics, or a related field. Expertise in statistical software (such as SAS, R, or Python), model validation frameworks, and relevant certifications like FRM or CFA are highly valuable. Critical thinking, attention to detail, and clear communication are crucial soft skills for evaluating risks and collaborating remotely with cross-functional teams. These abilities ensure accurate risk assessment, compliance with regulations, and effective communication of complex model findings in a remote work environment.

What are some common challenges faced by professionals in work from home model risk management roles, and how can they be addressed?

One common challenge in Work From Home Model Risk Management is maintaining effective communication and collaboration with cross-functional teams, such as data scientists, IT, and business stakeholders, when working remotely. This can be addressed by leveraging collaborative tools, scheduling regular virtual meetings, and establishing clear documentation practices. Another challenge is staying updated on emerging regulatory requirements and best practices, which can be managed by participating in webinars, online trainings, and professional forums. Being proactive in seeking feedback and maintaining a structured daily routine also helps ensure productivity and alignment with team goals.

What is the difference between Work From Home Model Risk Management vs Data Analyst?

AspectWork From Home Model Risk ManagementData Analyst
CredentialsRisk management certifications, industry-specific knowledgeStatistics, data analysis, and related certifications
Work EnvironmentRemote, focused on risk policies and complianceRemote or office, focused on data interpretation and reporting
Industry UsageFinancial, insurance, banking sectorsVarious industries including finance, marketing, healthcare
Search IntentRisk management, compliance, remote risk rolesData analysis, reporting, data-driven decision making

Work From Home Model Risk Management focuses on identifying and mitigating risks within remote operational models, often requiring risk certifications. Data Analysts interpret data to support business decisions, with a broader industry application. While both roles can be remote, their core functions and required skills differ significantly.

What are popular job titles related to Work From Home Model Risk Management jobs in Oregon?

For Work From Home Model Risk Management jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Work From Home Model Risk Management jobs in Oregon look for?

The top searched job categories for Work From Home Model Risk Management jobs in Oregon are:

What cities in Oregon are hiring for Work From Home Model Risk Management jobs?

Cities in Oregon with the most Work From Home Model Risk Management job openings:

Staff Machine Learning Model Risk Specialist

Upstart

OR • On-site, Remote

$98K/yr

Full-time

Posted 3 days ago

New


Upstart rating

7.6

Company rating: 7.6 out of 10

Based on 6 frontline employees who took The Breakroom Quiz


Job description

The Team: 

Upstart's Model Risk team is responsible for ensuring that the risk of models - including all models impacting the new Upstart Bank - is well-understood, monitored, and mitigated. For years, machine learning (ML) models have been the key, differentiating technology at Upstart and an exciting area of focus for the team, but we are also expanding our scope to include all modeling methodologies and Generative AI applications across the Bank. This work is essential for Upstart's internal risk management, ensuring that our models help us make better decisions and maintain credibility with external stakeholders such as our regulators and capital providers. The team's focus is on articulating sound model risk management principles and implementing them in collaboration with our peers on Upstart's Risk and Machine Learning teams. This work also includes explaining our models to stakeholders, supporting external validations, and conducting analyses to reinforce our goals.

As a Staff Model Risk Specialist at Upstart, you will independently execute core components of the model risk management program supporting Upstart Bank. You will oversee risk across a diverse and growing inventory of models and Generative AI applications, including sophisticated machine learning models used in lending and other models supporting areas such as fraud, compliance, finance, capital and liquidity, servicing, and operational risk.

This presents a unique opportunity to help build a comprehensive model risk management program for a new bank. You will evaluate model and GenAI application documentation, monitoring, governance, and risk assessments while partnering with developers, business sponsors, and risk stakeholders to identify and address emerging risks. You will apply a risk-based approach across technologies that range from traditional statistical methods to advanced machine learning and GenAI systems, adapting your review to their different purposes, complexities, and risk profiles. You will also translate complex technical concepts into clear, decision-useful information for audiences with varying levels of technical expertise.

How you'll make an impact

  • Partner with Machine Learning teams, GenAI application developers, business sponsors, and other stakeholders to maintain accurate inventories, risk assessments, documentation, monitoring reports, and supporting governance materials for models and GenAI applications affecting Upstart Bank.
  • Review methodologies, assumptions, data inputs, system designs, performance measures, controls, and limitations to provide effective challenge and identify areas requiring further analysis or remediation.
  • Apply a risk-based approach to evaluate a broad range of quantitative methods and technologies, from traditional statistical and financial models to complex machine learning models and GenAI applications.
  • Conduct and document model risk assessments, monitoring reviews, and targeted quantitative analyses that support internal policies and regulatory expectations.
  • Help develop practical governance approaches for new and rapidly evolving technologies, particularly machine learning and GenAI applications for which risks, evaluation methods, and industry practices continue to evolve.
  • Respond to model- and GenAI-related questions from regulators, lending partners, and other external stakeholders in collaboration with Machine Learning, business teams, Legal, Compliance, and partner-facing teams.
  • Track model risk issues, remediation plans, program goals, and emerging risks, escalating material findings and recommending practical improvements as the Bank's model inventory and use cases continue to expand.

Minimum Qualifications 

  • Master's degree in quantitative field such as finance, mathematics, economics, statistics or a related discipline
  • 4+ years of experience in model risk management, model validation, model governance, machine learning, data science, quantitative risk, AI governance, or a related technical risk function.
  • Internship or project experience related to model risk management, model validation, machine learning, or data science.
  • Basic understanding of AI/ML methodologies such as tree-based models and neural networks.
  • General familiarity with GenAI applications.
  • Experience coding in R, Python, or similar languages such as Matlab

Preferred Qualifications

  • PhD in a quantitative field of study such as statistics, econometrics, finance, mathematics; or a related discipline
  • 5+ years of experience in model risk management or model governance, or related fields such as ML and Data Science, Risk, Trust and Safety, or Technical Writing
  • Familiarity with GenAI applications, including evaluation approaches, prompt and system design, retrieval-augmented generation, tool use, guardrails, and ongoing monitoring.
  • Experience assessing models used outside of credit underwriting, such as models supporting fraud, compliance, finance, capital and liquidity, servicing, operational risk, or financial reporting.
  • Strong communication skills: ability to adapt technical information to varying needs and audiences, and managing trade-offs such as providing modeling detail while protecting intellectual property
  • Proactive mindset with the ability to take initiative 
  • Understanding of advanced AI/ML topics such as model monitoring, fairness, and explainability
  • Advanced coding skills in R, Python, and SQL, and experience using Git
  • Interest in or knowledge of consumer lending, credit risk, model fairness, explainability, or the use of machine learning and GenAI in a regulated environment.

Position location This role is available in the following locations: Remote

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions' cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

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#LI-MidSenior


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