Senior Model Risk Manager
Mercury is building the financial stack for startups. We’re here to make banking* intuitive, powerful, and safe for entrepreneurs and businesses of all sizes. Our team is obsessed with crafting thoughtful tools and protecting the financial ecosystem from fraud, money laundering, sanctions evasion, and other financial crimes. We’re seeking a detail-oriented, technically strong, and collaborative Senior Model Risk Manager to help us level up our defenses while enabling product velocity and innovation.
As a Senior Model Risk Manager, you will lead the validation, monitoring, and governance of rule-based detection models, data pipelines, vendor models and ML/AI models and tools. You’ll play a pivotal role in ensuring Mercury’s models are accurate, compliant, and robust, and support the continuous development of our model risk framework in alignment with regulatory expectations. This is a hands-on technical leadership role for someone who understands the nuances of financial crime typologies, risk analytics, and model lifecycle governance. You’ll collaborate closely with model developers, compliance leads, and engineering partners while reporting into the Head of Model Risk Management.
*Mercury is a financial technology company, not a bank. Banking services provided through Choice Financial Group, Column N.A., and Evolve Bank & Trust, Members FDIC.
Here are some of the things you will do:
Model Validation & Performance Oversight
Perform independent model validation with a focus of AML and sanctions models, including transaction monitoring, customer risk scoring, sanctions screening, related AI tools, etc.
Assess model methodologies, data integrity, assumptions, implementation, and output reasonableness.
Evaluate emerging modeling techniques, such as behavioral analytics and machine learning, for suitability in financial crime detection.
Ongoing Monitoring & Model Governance
Support the establishment and maintenance of monitoring plans for model performance, stability, and concept drift.
Lead periodic model reviews, recalibrations, and performance assessments in coordination with model owners.
Track model inventory, issue remediation, and documentation standards under SR 11-7 and internal governance requirements.
Controls & Risk Mitigation
Recommend risk mitigation strategies for model limitations, including compensating controls, overrides, and thresholds.
Participate in issue tracking, documentation, and validation of remediation evidence for model validation findings.
Regulatory & Stakeholder Support
Prepare model validation reports and technical summaries in response to requests from internal audit, executives, bank partners and regulators..
Partner with compliance and legal teams to ensure model alignment with regulatory standards (e.g., BSA/AML, OFAC, FATF, FinCEN).
Culture Building & Advocacy
Champion the development of model risk management as a core function within a fast-paced fintech environment.
Cultivate model risk principles, regulatory expectations, and the value of strong model governance among cross-functional teams including engineering, product, risk, and compliance
Ad-hoc Analysis & Cross-Functional Support
Assist with one-off data validation tasks to support timely and accurate compliance reporting to regulators and bank partners.
Engage in early risk identification efforts and provide MRM advice on the design and governance of new machine learning and AI models under development.
Flex into broader analytical or compliance-related requests as needed, supporting the evolving needs of a growing MRM function.
There are lots of paths that could lead you to be successful in a role like this; we think the strongest candidates will have some of these experiences or attributes:
Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Finance, or a related field. Master’s degree or PhD is preferred.
6–8 years of experience in model risk management, model development, quantitative analytics or data science.
2-4 years of experience in financial crimes related modeling and tuning techniques.
Strong command of statistical analysis and data validation methods; proficiency in SQL and Python. Knowledge of Haskell is a plus but not required.
Solid understanding of regulatory frameworks (e.g., SR 11-7, OCC 2011-12, FinCEN advisories).
Experience drafting validation reports, audit response materials, and stakeholder briefings.
Familiarity with Sanctions screening vendor tools (e.g., Bridger, Fircosoft, etc) is a plus.
Experience with Machine Learning and /or AI models is a plus.
CAMS, CRCM, or equivalent certification is a plus.
Critical thinking skills and investigative rigor when reviewing data, assumptions, and outputs.
A healthy dose of skepticism combined with a constructive, solution-oriented mindset.
Exceptional attention to detail across documentation, validation artifacts, and analysis.
Strong communication skills, including the ability to write clear, structured, and technically sound documentation.
Comfort in an ambiguous, fast-paced, and rapidly changing business and regulatory environment.
Ambitious sense of curiosity and willingness to explore how compliance and risk management impacts Mercury’s products and our customers outside of one’s comfort zone, such as new markets or financial products.
Respect for and interest in financial rules and regulations, as well as an eagerness to innovate and drive the industry forward.
The total rewards package at Mercury includes base salary, equity, and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.
Our target new hire base salary ranges for this role are the following:
US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $200,700 - $250,900
US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $180,600 - $225,800
Canadian employees (any location): CAD $189,700 - $237,100
Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.
We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here.
#LI-HC1
About the job
Apply for this position
Senior Model Risk Manager
Mercury is building the financial stack for startups. We’re here to make banking* intuitive, powerful, and safe for entrepreneurs and businesses of all sizes. Our team is obsessed with crafting thoughtful tools and protecting the financial ecosystem from fraud, money laundering, sanctions evasion, and other financial crimes. We’re seeking a detail-oriented, technically strong, and collaborative Senior Model Risk Manager to help us level up our defenses while enabling product velocity and innovation.
As a Senior Model Risk Manager, you will lead the validation, monitoring, and governance of rule-based detection models, data pipelines, vendor models and ML/AI models and tools. You’ll play a pivotal role in ensuring Mercury’s models are accurate, compliant, and robust, and support the continuous development of our model risk framework in alignment with regulatory expectations. This is a hands-on technical leadership role for someone who understands the nuances of financial crime typologies, risk analytics, and model lifecycle governance. You’ll collaborate closely with model developers, compliance leads, and engineering partners while reporting into the Head of Model Risk Management.
*Mercury is a financial technology company, not a bank. Banking services provided through Choice Financial Group, Column N.A., and Evolve Bank & Trust, Members FDIC.
Here are some of the things you will do:
Model Validation & Performance Oversight
Perform independent model validation with a focus of AML and sanctions models, including transaction monitoring, customer risk scoring, sanctions screening, related AI tools, etc.
Assess model methodologies, data integrity, assumptions, implementation, and output reasonableness.
Evaluate emerging modeling techniques, such as behavioral analytics and machine learning, for suitability in financial crime detection.
Ongoing Monitoring & Model Governance
Support the establishment and maintenance of monitoring plans for model performance, stability, and concept drift.
Lead periodic model reviews, recalibrations, and performance assessments in coordination with model owners.
Track model inventory, issue remediation, and documentation standards under SR 11-7 and internal governance requirements.
Controls & Risk Mitigation
Recommend risk mitigation strategies for model limitations, including compensating controls, overrides, and thresholds.
Participate in issue tracking, documentation, and validation of remediation evidence for model validation findings.
Regulatory & Stakeholder Support
Prepare model validation reports and technical summaries in response to requests from internal audit, executives, bank partners and regulators..
Partner with compliance and legal teams to ensure model alignment with regulatory standards (e.g., BSA/AML, OFAC, FATF, FinCEN).
Culture Building & Advocacy
Champion the development of model risk management as a core function within a fast-paced fintech environment.
Cultivate model risk principles, regulatory expectations, and the value of strong model governance among cross-functional teams including engineering, product, risk, and compliance
Ad-hoc Analysis & Cross-Functional Support
Assist with one-off data validation tasks to support timely and accurate compliance reporting to regulators and bank partners.
Engage in early risk identification efforts and provide MRM advice on the design and governance of new machine learning and AI models under development.
Flex into broader analytical or compliance-related requests as needed, supporting the evolving needs of a growing MRM function.
There are lots of paths that could lead you to be successful in a role like this; we think the strongest candidates will have some of these experiences or attributes:
Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Finance, or a related field. Master’s degree or PhD is preferred.
6–8 years of experience in model risk management, model development, quantitative analytics or data science.
2-4 years of experience in financial crimes related modeling and tuning techniques.
Strong command of statistical analysis and data validation methods; proficiency in SQL and Python. Knowledge of Haskell is a plus but not required.
Solid understanding of regulatory frameworks (e.g., SR 11-7, OCC 2011-12, FinCEN advisories).
Experience drafting validation reports, audit response materials, and stakeholder briefings.
Familiarity with Sanctions screening vendor tools (e.g., Bridger, Fircosoft, etc) is a plus.
Experience with Machine Learning and /or AI models is a plus.
CAMS, CRCM, or equivalent certification is a plus.
Critical thinking skills and investigative rigor when reviewing data, assumptions, and outputs.
A healthy dose of skepticism combined with a constructive, solution-oriented mindset.
Exceptional attention to detail across documentation, validation artifacts, and analysis.
Strong communication skills, including the ability to write clear, structured, and technically sound documentation.
Comfort in an ambiguous, fast-paced, and rapidly changing business and regulatory environment.
Ambitious sense of curiosity and willingness to explore how compliance and risk management impacts Mercury’s products and our customers outside of one’s comfort zone, such as new markets or financial products.
Respect for and interest in financial rules and regulations, as well as an eagerness to innovate and drive the industry forward.
The total rewards package at Mercury includes base salary, equity, and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.
Our target new hire base salary ranges for this role are the following:
US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $200,700 - $250,900
US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $180,600 - $225,800
Canadian employees (any location): CAD $189,700 - $237,100
Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.
We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here.
#LI-HC1