Finance H-1B Sponsorship Jobs in Wisconsin
Finance H-1B visa sponsorship jobs in Wisconsin are concentrated in Milwaukee, Madison, and Green Bay, where employers like Northwestern Mutual, Fiserv, Associated Bank, and Johnson Financial Group regularly hire international professionals. Roles in financial analysis, risk management, actuarial science, and compliance are among the most common H-1B positions in the state's financial services sector.
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Get Access To All JobsManager, Data & Context Governance
About BetaNXT
BetaNXT is a leading provider of frictionless wealth management infrastructure, real-time data solutions, and an enhanced advisor experience. We invest in platforms, products, and partnerships to accelerate growth for the ecosystem we serve. Our connective approach empowers our clients to deliver a comprehensive, end-to-end advisor and investor experience. BetaNXT is a premier provider of technology, data, and operations as services to a rich client base of wealth managers, institutional wealth firms, and digital brokers, providing end-to-end solutions across the investment lifecycle.
Position Overview
BetaNXT is expanding its data governance function to meet the demands of a rapidly evolving data and AI landscape. We are seeking a Manager, Data & Context Governance to build and lead a team of data stewards and integration specialists responsible for both traditional data governance and a new, equally critical discipline: context governance — ensuring the information, definitions, and business context that power our AI and LLM-driven systems and products are accurate, complete, and trustworthy. This Manager will hire, lead, and develop a dedicated team, with each team member aligned to a functional business domain, owning governance outcomes for both structured data assets and the context that drives AI-generated outputs. Beyond installing sound governance practice, this Manager is expected to operate as a strategic partner and execution driver across BetaNXT’s active data and AI initiatives — working hands-on with project teams to ensure governance is built into delivery from the start, not bolted on afterward.
Duties and Responsibilities
Team Leadership & Structure
- Build, lead, and develop a team of data stewards and integration specialists, each aligned to a functional business domain (e.g., Trading, Accounts, Positions, Pricing) as their primary partner area.
- Define role clarity, workload distribution, and performance expectations for team members covering both traditional data governance and context/AI governance responsibilities.
- Serve as the escalation point and quality bar-setter for team output across all domains, owning the end-to-end result even where day-to-day work is delegated.
Strategic Data Governance
- Develop and execute a data governance strategy that spans structured data assets and the broader context assets (definitions, business rules, taxonomies, knowledge sources) that feed AI and LLM systems and products.
- Partner directly with product, architecture, and business stakeholders across data and AI initiatives (including the Data Integration Hub) to embed governance requirements into project planning and execution, rather than governing after the fact.
- Own strategic direction for the data governance tooling, ensuring it is configured and maintained to achieve intended data governance and context governance outcomes (module ownership sits with this Manager; platform architecture is owned separately within the team).
Context Governance
- Establish governance practices for the context that drives AI/LLM outputs, including:
- Curating and maintaining the knowledge sources, definitions, and business rules that feed AI/LLM systems and products.
- Overseeing validation and quality review of AI-generated outputs against approved source context.
- Establishing governance standards for prompt and agent-instruction design where it affects output accuracy and consistency.
- Define what “good context” looks like for each business domain and ensure the team applies consistent standards across domains.
Data Stewardship Program
- Design and operationalize a dedicated stewardship model, with clear roles, responsibilities, and processes across both data and context governance.
- Define domain-alignment structures that connect each team member to the functional business area(s) they support.
Data Quality & Metadata Management
- Define and oversee data quality standards, processes, and metrics for structured data assets.
- Ensure the completeness and accuracy of the data catalog, data dictionary, and related metadata artifacts.
Data Privacy and Compliance
- Ensure governance practices support compliance with relevant data protection and industry regulations.
Metrics & Reporting
- Establish and report on KPIs spanning both governance disciplines, including:
- Traditional metrics: catalog/metadata completeness, team SLA adherence, data quality issue resolution.
- AI-output metrics: accuracy/groundedness of AI-driven outputs, reduction in escalations or hallucination-related incidents tied to context gaps.
- Provide regular reporting to leadership on governance program health and business impact.
Training, Change Management & Continuous Improvement
- Develop training and enablement to raise data and context literacy across the organization.
- Lead change management to integrate governance practices into existing workflows.
- Continuously evaluate and refine governance processes as business needs and AI capabilities evolve.
Skills and Experience
- 3+ years in a leadership role within data governance, with direct people-management experience.
- 10+ years in enterprise data teams, with substantial experience in financial services, banking, or wealth management.
- Strong understanding of data governance principles, metadata management, data quality, and data stewardship.
- Familiarity with data governance tools and technologies (e.g., Data.World, Informatica, Collibra, Alation).
- Working knowledge of how LLM/AI systems consume context (retrieval sources, knowledge bases, prompt/agent design) and how gaps in context affect output quality — prior hands-on AI/LLM governance experience is a strong plus but not required.
- Proven ability to build and lead a team from the ground up, including defining new roles and operating models.
- Excellent understanding of regulatory requirements related to data privacy and security.
- Exceptional leadership and communication skills, with the ability to influence across all organizational levels and act as a strategic partner to project teams, not solely a governance-office function.
- Strong documentation skills to maintain clear records of governance processes, policies, and decisions.
Manager, Data & Context Governance
About BetaNXT
BetaNXT is a leading provider of frictionless wealth management infrastructure, real-time data solutions, and an enhanced advisor experience. We invest in platforms, products, and partnerships to accelerate growth for the ecosystem we serve. Our connective approach empowers our clients to deliver a comprehensive, end-to-end advisor and investor experience. BetaNXT is a premier provider of technology, data, and operations as services to a rich client base of wealth managers, institutional wealth firms, and digital brokers, providing end-to-end solutions across the investment lifecycle.
Position Overview
BetaNXT is expanding its data governance function to meet the demands of a rapidly evolving data and AI landscape. We are seeking a Manager, Data & Context Governance to build and lead a team of data stewards and integration specialists responsible for both traditional data governance and a new, equally critical discipline: context governance — ensuring the information, definitions, and business context that power our AI and LLM-driven systems and products are accurate, complete, and trustworthy. This Manager will hire, lead, and develop a dedicated team, with each team member aligned to a functional business domain, owning governance outcomes for both structured data assets and the context that drives AI-generated outputs. Beyond installing sound governance practice, this Manager is expected to operate as a strategic partner and execution driver across BetaNXT’s active data and AI initiatives — working hands-on with project teams to ensure governance is built into delivery from the start, not bolted on afterward.
Duties and Responsibilities
Team Leadership & Structure
- Build, lead, and develop a team of data stewards and integration specialists, each aligned to a functional business domain (e.g., Trading, Accounts, Positions, Pricing) as their primary partner area.
- Define role clarity, workload distribution, and performance expectations for team members covering both traditional data governance and context/AI governance responsibilities.
- Serve as the escalation point and quality bar-setter for team output across all domains, owning the end-to-end result even where day-to-day work is delegated.
Strategic Data Governance
- Develop and execute a data governance strategy that spans structured data assets and the broader context assets (definitions, business rules, taxonomies, knowledge sources) that feed AI and LLM systems and products.
- Partner directly with product, architecture, and business stakeholders across data and AI initiatives (including the Data Integration Hub) to embed governance requirements into project planning and execution, rather than governing after the fact.
- Own strategic direction for the data governance tooling, ensuring it is configured and maintained to achieve intended data governance and context governance outcomes (module ownership sits with this Manager; platform architecture is owned separately within the team).
Context Governance
- Establish governance practices for the context that drives AI/LLM outputs, including:
- Curating and maintaining the knowledge sources, definitions, and business rules that feed AI/LLM systems and products.
- Overseeing validation and quality review of AI-generated outputs against approved source context.
- Establishing governance standards for prompt and agent-instruction design where it affects output accuracy and consistency.
- Define what “good context” looks like for each business domain and ensure the team applies consistent standards across domains.
Data Stewardship Program
- Design and operationalize a dedicated stewardship model, with clear roles, responsibilities, and processes across both data and context governance.
- Define domain-alignment structures that connect each team member to the functional business area(s) they support.
Data Quality & Metadata Management
- Define and oversee data quality standards, processes, and metrics for structured data assets.
- Ensure the completeness and accuracy of the data catalog, data dictionary, and related metadata artifacts.
Data Privacy and Compliance
- Ensure governance practices support compliance with relevant data protection and industry regulations.
Metrics & Reporting
- Establish and report on KPIs spanning both governance disciplines, including:
- Traditional metrics: catalog/metadata completeness, team SLA adherence, data quality issue resolution.
- AI-output metrics: accuracy/groundedness of AI-driven outputs, reduction in escalations or hallucination-related incidents tied to context gaps.
- Provide regular reporting to leadership on governance program health and business impact.
Training, Change Management & Continuous Improvement
- Develop training and enablement to raise data and context literacy across the organization.
- Lead change management to integrate governance practices into existing workflows.
- Continuously evaluate and refine governance processes as business needs and AI capabilities evolve.
Skills and Experience
- 3+ years in a leadership role within data governance, with direct people-management experience.
- 10+ years in enterprise data teams, with substantial experience in financial services, banking, or wealth management.
- Strong understanding of data governance principles, metadata management, data quality, and data stewardship.
- Familiarity with data governance tools and technologies (e.g., Data.World, Informatica, Collibra, Alation).
- Working knowledge of how LLM/AI systems consume context (retrieval sources, knowledge bases, prompt/agent design) and how gaps in context affect output quality — prior hands-on AI/LLM governance experience is a strong plus but not required.
- Proven ability to build and lead a team from the ground up, including defining new roles and operating models.
- Excellent understanding of regulatory requirements related to data privacy and security.
- Exceptional leadership and communication skills, with the ability to influence across all organizational levels and act as a strategic partner to project teams, not solely a governance-office function.
- Strong documentation skills to maintain clear records of governance processes, policies, and decisions.
H-1B Finance Job Roles in Wisconsin
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Search Finance Jobs in WisconsinFinance H-1B Sponsorship Jobs in Wisconsin: Frequently Asked Questions
Which finance companies sponsor H-1B visas in Wisconsin?
Northwestern Mutual, Fiserv, Associated Bank, Johnson Financial Group, and Baird are among the Wisconsin-based financial services employers with documented H-1B visa sponsorship histories. Larger regional banks and insurance firms tend to sponsor more consistently than smaller credit unions or independent advisories, which may lack the HR infrastructure to manage the petitioning process.
Which cities in Wisconsin have the most finance H-1B sponsorship jobs?
Milwaukee is Wisconsin's financial hub and accounts for the largest share of finance H-1B positions, driven by its concentration of insurance firms, investment companies, and financial technology employers. Madison supports a secondary market, particularly in fintech and financial compliance roles tied to the state government and university sector. Green Bay and Waukesha see more limited but consistent activity.
What types of finance roles typically qualify for H-1B sponsorship?
Roles that qualify as specialty occupations under H-1B rules are those requiring at least a bachelor's degree in a specific field. In finance, this commonly includes financial analysts, quantitative analysts, actuaries, risk managers, compliance officers, and corporate finance associates. Positions where any general degree satisfies the requirement, such as broad sales or relationship management roles, face more scrutiny.
How do I find finance H-1B sponsorship jobs in Wisconsin?
Migrate Mate is built specifically for this search. You can filter by visa type, industry, and state to surface finance H-1B sponsorship jobs in Wisconsin from employers with verified sponsorship histories. This is more targeted than a general job search, since most platforms don't filter by visa sponsorship willingness at all, which saves significant time when your situation requires it.
Are there any Wisconsin-specific considerations for H-1B sponsorship in finance?
Wisconsin's financial services sector is dominated by insurance and wealth management firms rather than large investment banks, which affects the types of H-1B roles available. Many Wisconsin employers sponsor H-1B holders for the first time when they find the right candidate, so a job posting not explicitly mentioning sponsorship doesn't necessarily mean the employer won't consider it. Prevailing wage requirements still apply statewide and are determined by the specific county and job title.
What is the prevailing wage for H-1B finance jobs in Wisconsin?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.