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Model Validation Manager Jobs in Minnesota (NOW HIRING)

... and validation * Experience with data profiling and data quality assessment * Ability to translate complex business concepts into structured data models * Familiarity with metadata management ...

... and validation * Experience with data profiling and data quality assessment * Ability to translate complex business concepts into structured data models * Familiarity with metadata management ...

Lead Systems Engineer

Saint Paul, MN · On-site

$150K - $220K/yr

... management, and verification and validation efforts. This role will include complex and multi-disciplinary problem solving. This position involves fostering the integration of Model-Based Systems ...

AI Product Manager Location: Chanhassen, MN (Hybrid - Onsite & Remote) Type: Contract | Full-Time ... Collaborate with data scientists to validate models and guide experimentation. * Own the AI product ...

Senior Manager, Product Management

Minneapolis, MN · On-site

$132K - $174K/yr

Anaplan is seeking a passionate, experienced Senior Manager, Product Management to lead a team ... Leverage your deep Anaplan model-building expertise to guide your team in validating complex ...

Showing results 41-60

Model Validation Manager information

See Minnesota salary details

$46.5K

$103.2K

$157.2K

How much do model validation manager jobs pay per year?

As of Aug 6, 2026, the average yearly pay for model validation manager in Minnesota is $103,245.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,000.00 and $129,300.00 per year, depending on experience, location, and employer.

How does a model validation manager collaborate with other teams during the model validation process?

A Model Validation Manager works closely with model developers, risk management teams, and internal audit to ensure models meet regulatory and business standards. Collaboration often involves reviewing model documentation, discussing model assumptions and methodologies, and providing feedback for improvements. Effective cross-functional communication is essential, as validation managers must balance technical analysis with regulatory compliance and business objectives. Regular meetings and clear reporting lines help facilitate this collaboration, ensuring that model risks are identified and addressed promptly.

What is the difference between Model Validation Manager vs Quantitative Analyst?

AspectModel Validation ManagerQuantitative Analyst
CredentialsTypically requires advanced degrees in finance, mathematics, or statistics; certifications like CFA or FRM are commonOften holds degrees in finance, economics, or mathematics; certifications like CFA are also common
Work EnvironmentWorks in risk management, model validation teams within banks or financial institutionsWorks in trading, investment analysis, or risk departments within financial firms
Industry UsagePrimarily in banking, asset management, and financial services for model risk assessmentAcross investment firms, hedge funds, and banks for market analysis and trading strategies

The Model Validation Manager focuses on reviewing and validating financial models to ensure accuracy and compliance, often working within risk management teams. In contrast, a Quantitative Analyst develops and applies mathematical models for trading, investment, or risk purposes. While both roles require strong quantitative skills and similar credentials, their core responsibilities and work environments differ significantly.

What skills and qualifications are needed to be a model validation manager?

To thrive as a Model Validation Manager, you need strong quantitative analysis skills, knowledge of risk management, and an advanced degree in mathematics, statistics, finance, or a related field. Familiarity with technical tools such as Python, R, SAS, and model risk management frameworks, as well as experience with regulatory compliance, is typically required. Exceptional problem-solving, communication, and stakeholder management abilities are important soft skills for this role. These skills ensure effective validation of financial models, regulatory compliance, and clear communication of complex findings to non-technical audiences.

What does a model validation manager do?

A Model Validation Manager is responsible for overseeing the validation of financial, risk, or predictive models within an organization. Their primary duties include ensuring that models are accurate, reliable, and compliant with regulatory requirements. They lead teams that assess model performance, identify potential weaknesses, and recommend improvements. This role helps maintain the integrity of models used in decision-making processes, particularly in industries like banking and finance.
What are the most commonly searched types of Model Validation jobs in Minnesota? The most popular types of Model Validation jobs in Minnesota are:
What are popular job titles related to Model Validation Manager jobs in Minnesota? For Model Validation Manager jobs in Minnesota, the most frequently searched job titles are:
Infographic showing various Model Validation Manager job openings in Minnesota as of July 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $103,245 per year, or $49.6 per hour.

Senior Data Modeler (Snowflake)

Expleo

Minneapolis, MN • On-site

$96 - $106/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Job description

Overview

Location: Onsite (Minneapolis, MN)

Employment Type: Full-Time

Shape Modern Data Foundations with Snowflake

Are you a seasoned Data Modeler who loves turning complex business processes into clean, scalable data structures? Trissential is partnering with a forwardthinking enterprise client to bring on a Senior Data Modeler who will play a critical role in designing and evolving data models within a modern Snowflakecentric data ecosystem.

If you thrive in modern cloud data environments and enjoy collaborating across technical and business teams, this role was built for you.

What's in It for You?

  • HighImpact Modeling Work - Design enterpriselevel data models that power analytics, reporting, and data products
  • Modern Cloud Stack - Work handson with Snowflake and cloudbased data platforms
  • Strategic Visibility - Partner with data engineering, analytics, and governance teams on core data decisions
  • Modeling Ownership - Influence data standards, structure, and quality across the organization
  • Career Growth - Expand your Snowflake and enterprise data modeling expertise in a mature data environment
  • Collaborative Culture - Join a team that values clarity, data quality, and thoughtful design

Your Role & Responsibilities

You will:

  • Lead the endtoend data modeling lifecycle, from conceptual through physical models
  • Design logical and physical data models optimized for Snowflake and analytical workloads
  • Translate business requirements into clear, scalable data structures
  • Partner with data engineers to ensure models are efficiently implemented in Snowflake
  • Support modeltosource and modeltotarget mappings
  • Ensure models support performance, scalability, and secure data access
  • Maintain data dictionaries, lineage documentation, and metadata artifacts
  • Collaborate with data governance teams on naming standards and data quality rules
  • Participate in design reviews, change management, and impact analysis for data changes

Skills & Experience You Should Possess

  • 10+ years of experience in data modeling, data analysis, or advanced data roles
  • Strong expertise in conceptual, logical, and physical data modeling
  • Handson experience modeling data in Snowflake or similar cloud data platforms
  • Strong SQL skills for data analysis and validation
  • Experience with data profiling and data quality assessment
  • Ability to translate complex business concepts into structured data models
  • Familiarity with metadata management, lineage, and governance concepts
  • Strong communication skills across technical and nontechnical audiences

Bonus Points If You Have

  • Python experience for data profiling or analysis
  • Experience working with columnar or lakehouse architectures
  • Ability to interpret semistructured data (JSON, etc.)
  • Exposure to enterprise data standards or data cataloging tools

Education & Certifications You Need

  • Bachelor's degree in Computer Science, Information Systems, Data Management, or a related field
  • Data modeling or data governance certifications are a plus, but not required

What We Offer

At Trissential, we believe great data work happens when talented people are supported, valued, and empowered. When you join our client's team through Trissential, you gain access to meaningful work and a strong benefits package.

Competitive Compensation - $96-$106 per hour. Final compensation is determined based on skill alignment, years of experience, and fair, marketbased rates by geography. Comprehensive Benefits for you and your dependents - Medical, dental, vision, free telehealth, HSA with company contribution, life and disability insurance, and 401k with matching Paid Time Off - Offers paid time away from work Career Development - Mentorship, handson learning, and exposure to enterprisescale data initiatives Inclusive Team Culture - Built on collaboration, integrity, and technical excellence

 

This role is only open to individuals who are authorized to work in the United States.

Ready to design the data that drives real decisions?

Apply today and take the next step in your career as a Senior Data Modeler (Snowflake) with Trissential.

Employment Type: OTHER