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Senior Manager Data Analytics Jobs in Amherst, WI

Sr. Technical Manager

Stevens Point, WI · On-site

$110K - $152K/yr

Sr. Technical Manager Mativ is a global leader in specialty materials headquartered in Alpharetta ... Strong problem solving, quantitative, analytical skills. * Strong skills in various applications ...

New

Cost Accountant

Mosinee, WI · On-site

$64K - $86K/yr

Collaborate with department managers and senior leadership to review financial performance. * Conduct in-depth production data analysis, identifying key cost drivers and variances. * Analyze labor ...

Cost Accountant

Mosinee, WI · On-site

$64K - $86K/yr

Collaborate with department managers and senior leadership to review financial performance. * Conduct in-depth production data analysis, identifying key cost drivers and variances. * Analyze labor ...

Geospatial Data Management & Mapping * Develop and maintain GIS maps and databases for transmission ... Perform spatial analysis including buffer analysis, route comparisons, conflict identification, and ...

Sr. Technical Manager

Stevens Point, WI · On-site

$110K - $152K/yr

The Senior Technical Manager is responsible for maintaining customer satisfaction expectations for ... Strong problem solving, quantitative, analytical skills. * Strong skills in various applications ...

New

Showing results 21-40

Senior Manager Data Analytics information

See Amherst, WI salary details

$43.8K

$111.3K

$163.9K

How much do senior manager data analytics jobs pay per year?

As of Sep 7, 2026, the average yearly pay for senior manager data analytics in Amherst, WI is $111,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,900.00 and $131,300.00 per year, depending on experience, location, and employer.

What does a senior manager data analytics do?

A Senior Manager Data Analytics leads teams that analyze large sets of data to help organizations make informed business decisions. They develop analytics strategies, oversee data projects, and ensure the quality and integrity of data-driven insights. This role often involves collaborating with other departments, mentoring analysts, and presenting key findings to senior leadership. Senior Managers in this field need strong technical skills, leadership abilities, and business acumen to drive impactful results.

What are the key skills and qualifications needed to thrive as a senior manager data analytics?

To thrive as a Senior Manager Data Analytics, you need advanced expertise in data analysis, statistical modeling, and business intelligence, typically supported by a degree in a quantitative field and several years of analytics experience. Proficiency with analytics tools such as SQL, Python, R, and platforms like Tableau or Power BI, as well as experience with data warehousing systems, is essential. Strong leadership, strategic thinking, and communication skills enable you to guide teams and translate complex findings into actionable business insights. These competencies are crucial for driving data-informed decision-making and maximizing organizational value from analytics initiatives.

How does a senior manager data analytics typically collaborate with cross-functional teams within an organization?

Senior Managers of Data Analytics frequently work alongside cross-functional teams such as IT, product development, marketing, and finance to ensure that data-driven insights align with business objectives. They are responsible for translating complex analytical findings into actionable recommendations and communicating these insights clearly to both technical and non-technical stakeholders. Regular collaboration often involves leading meetings, setting project priorities, and ensuring data initiatives are integrated smoothly with ongoing business strategies. This collaborative environment fosters innovation and helps drive organizational growth.

What is the difference between Senior Manager Data Analytics vs Data Analyst?

AspectSenior Manager Data AnalyticsData Analyst
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related field; extensive experienceBachelor's degree in related field; entry to mid-level experience
Work EnvironmentLeadership roles, strategic planning, team managementData collection, analysis, reporting
Employer & Industry UsageCorporate, finance, healthcare, tech companiesVarious industries, including marketing, finance, tech
Common Search & ComparisonOften compared for leadership and strategic rolesCompared for technical and analytical skills

The main difference between Senior Manager Data Analytics and Data Analyst lies in their responsibilities and experience level. Senior Managers focus on strategic oversight, team leadership, and decision-making, while Data Analysts handle data collection, analysis, and reporting at a more technical level. Senior Managers typically have more experience and credentials, working in leadership roles within organizations across various industries.

What cities near Amherst, WI are hiring for Senior Manager Data Analytics jobs?

Cities near Amherst, WI with the most Senior Manager Data Analytics job openings:

Infographic showing various Senior Manager Data Analytics job openings in Amherst, WI as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $111,333 per year, or $53.5 per hour.

Lead - Insurance Underwriting & Loss Ontology

Acrisure

Stevens Point, WI • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Acrisure rating

7.5

Company rating: 7.5 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

226th of 315 rated insurance


Job description

Lead - Insurance Underwriting & Loss Ontology

Onsite 4 days per week

Note: This is a full-time role and we do not offer C2C or C2H employment and are not able to sponsor visas for this position.

About Acrisure

Acrisure Enterprise Technology Group is where human expertise meets advanced technology.

A global fintech leader, Acrisure empowers millions of ambitious businesses and individuals with the right solutions to grow boldly forward. Bringing cutting-edge technology and top-tier human support together, we connect clients with customized solutions across a range of insurance, reinsurance, payroll, benefits, cybersecurity, mortgage services - and more.

In the last twelve years, Acrisure has grown in revenue from $38 million to almost $5 billion and employs over 19,000 colleagues in more than 20 countries. Acrisure was built on entrepreneurial spirit. Prioritizing leadership, accountability, and collaboration, we equip our teams to work at the highest levels possible.

The Acrisure Data Ontology Department is a centralized function that defines and governs the enterprise's shared business language, data concepts, and relationships to ensure consistent use of data across systems, reporting, and operations. Combining ontology design, governance, master data management, and embedded subject matter expertise across core business domains, the department serves as the semantic bridge between business and technology-establishing canonical definitions, structuring enterprise data, enabling aligned system integration, and standardizing analytics logic through consistent dimensions, measures, and derived properties. This integrated approach enables accurate modeling of business concepts, faster resolution of ambiguity, and stronger alignment across integrations, analytics, and enterprise transformation, while supporting scalable standardization, data quality, and AI.

The Lead - Insurance Underwriting & Loss Ontology is responsible for defining, governing, and advancing the enterprise ontology supporting insurance coverage, exposure, underwriting, claims, and loss information across Acrisure's retail brokerage, wholesale, and specialty insurance businesses. Embedded within the Acrisure Data Ontology Department, this domain expert ensures consistent business meaning, semantic alignment, and data integrity across operational systems, data integrations, master data, analytics, and AI-driven applications. Working closely with business leaders, application owners, product teams, and data consumers, the role enables a unified and scalable foundation for insurance data management and decision-making across the enterprise.

Core Functions:

1. Develop & Manage Domain Ontology: Develop and manage the Coverage, Exposure, Underwriting, Claims, and Loss domain ontology, including enterprise data models, schemas, data dictionaries, naming standards, business definitions, classifications, hierarchies, and business logic. Ensure domain structures accurately represent insurance risk, coverage, exposure, underwriting, and loss concepts while supporting consistent use across Acrisure's retail, wholesale, and specialty business units.

2. Integrate Internal, Carrier & Third-Party Data: Design data integration of first-party, secondparty, and third-party data into the Coverage, Exposure, Underwriting, Claims, and Loss ontology. Establish standards and mappings for internal business data, carrier and market data, IVANS transactions, loss runs, valuation data, catastrophe and geospatial data, industry benchmarks, and other external data sources. Ensure all data is accurately aligned to ontology standards, business definitions, and domain schemas to create a unified, trusted view of insurance risk, exposure, underwriting performance, and loss experience across the enterprise.

3. Govern Critical Insurance Data: Establish and maintain governance standards for underwriting, exposure, coverage, claims, and loss data by identifying authoritative sources, defining business rules, managing data quality requirements, and resolving inconsistencies in definitions, classifications, and data usage. Ensure critical insurance data remains trusted, standardized, and fit for enterprise reporting, analytics, and operational use.

4. Align Domain Data: Lead the identification, onboarding, and alignment of underwriting, policy, claims, carrier, exposure, and loss data from source systems across Acrisure's retail, wholesale, and specialty business units. Partner with business and technology stakeholders to discover new data sources, define ontology mappings, and ensure data is extracted, transformed, and conformed to enterprise ontology standards. Establish and maintain lineage, business rules, and data requirements that enable trusted, consistent domain data to be consumed across reporting, analytics, AI, and operational workflows.

5. Enable Analytics & AI: Partner with analytics, reporting, data science, and technology teams to translate underwriting and loss business concepts into trusted data assets, metrics, and derived calculations. Ensure consistent definitions and business logic for key performance indicators, profitability analysis, portfolio management, loss reporting, predictive models, AI solutions, and enterprise decision-making.

6. Monitor Industry Standards & Data Requirements: Maintain deep expertise in insurance industry data standards, regulatory requirements, carrier reporting specifications, and market data exchange frameworks. Stay current on evolving standards such as ACORD, IVANS, carrier data requirements, and regulatory reporting obligations to ensure the ontology supports the accurate creation and exchange of policy documents, applications, submissions, binders, certificates of insurance, evidence of coverage, proofs of insurance, loss reporting, and other operational and regulatory insurance transactions. Partner with business and technology teams to proactively incorporate industry changes into ontology models, data definitions, and business rules.

Core Relationships: For the Lead - Insurance Underwriting & Loss Ontology, the core relationships and stakeholders reflect the groups that create, manage, consume, analyze, and govern underwriting and loss-related data across the enterprise.

1. Underwriting Leaders & Teams: Partner with underwriting leaders and subject matter experts to define exposure, coverage, risk assessment, pricing, and profitability concepts within the ontology. Ensure underwriting requirements, risk evaluation methodologies, carrier submission processes, and portfolio management metrics are accurately represented in enterprise data models and business definitions.

2. Claims Leaders & Teams: Collaborate with claims leadership and operations teams to establish consistent definitions for claims, reserves, payments, recoveries, cause of loss, severity, and loss development metrics. Ensure claims and loss data are accurately represented within the ontology to support claims operations, loss analysis, and performance reporting.

3. Agency, Wholesale & Specialty Business Leaders: Work closely with retail, wholesale, MGA, and specialty business leaders to understand unique underwriting, coverage, exposure, and claims processes across business units. Ensure the ontology accommodates business-specific requirements while maintaining enterprise consistency and standardization.

4. Carrier Partners & Market Relationships: Partner with carrier stakeholders to understand carrier-specific coverage structures, underwriting requirements, loss reporting standards, appetite data, submission requirements, and policy administration practices. Ensure carrier data can be standardized and integrated into the enterprise ontology while preserving critical business context.

5. Data & Analytics Teams: Collaborate with analytics, business intelligence, data science, and actuarial teams to define trusted metrics, dimensions, derived attributes, and business logic. Ensure underwriting, exposure, coverage, and loss data can be consistently leveraged for reporting, forecasting, profitability analysis, AI, and advanced analytics initiatives.

6. Technology & Enterprise Architecture Teams: Partner with enterprise architecture, application owners, integration teams, and engineering organizations to align source system data with ontology standards. Provide business definitions, mappings, lineage requirements, and domain expertise that support enterprise data products, workflows, and technology solutions.

7. Data Governance & Master Data Management: Work with data governance, MDM, data quality, and stewardship teams to establish authoritative sources, data ownership, governance policies, and quality standards for coverage, exposure, underwriting, claims, and loss information across the enterprise.

8. External Data & Industry Partners: Collaborate with providers of carrier, IVANS, catastrophe, geospatial, valuation, benchmarking, and other third-party insurance data to ensure external data sources are properly understood, standardized, and incorporated into the ontology in support of underwriting, risk management, and loss analysis.

9. Legal, Compliance & Regulatory Teams: Partner with legal, compliance, and regulatory stakeholders to ensure ontology structures and business definitions support insurance regulatory requirements, carrier reporting obligations, audits, certificates, evidence of coverage, and other compliance-related processes.

10. Product, Workflow & AI Solution Owners: Work with product managers, workflow owners, and AI solution teams to ensure coverage, exposure, underwriting, and loss concepts are accurately represented and consumable across enterprise applications, operational workflows, digital experiences, reporting platforms, and AI-powered business solutions.

Core Applications Supported: Provide domain expertise, data alignment, and ongoing support for key applications including the external portals and other core submission and underwriting applications to ensure consistent data usage and adherence to ontology and industry standards. Qualifications Deep expertise in how insurance risk is evaluated, bound, serviced, and ultimately produces loss outcomes. Ideal candidates have operational business knowledge, data governance, analytics enablement, and cross-system data integration experience.

1. Insurance Coverage Expertise

Deep knowledge of commercial and personal lines insurance coverages across retail, wholesale, and specialty business units.

Understanding of policy structures, coverages, endorsements, exclusions, limits, deductibles, sublimits, and conditions.

Ability to interpret carrier forms, manuscript forms, and policy language.

Knowledge of how coverages vary by carrier, product, state, and program.

2. Exposure Data Expertise

Expertise in the exposure information used to evaluate and price risk.

Understanding of insured locations, operations, property values, payroll, sales, vehicle schedules, employee counts, occupancy, classifications, and industry-specific exposures.

Knowledge of underwriting submission data captured through ACORD forms and carrier applications.

Ability to standardize and govern exposure data across diverse business units and source systems.

3. Underwriting Expertise

Understanding of underwriting workflows from submission through quote, bind, issuance, renewal, and endorsement.

Knowledge of underwriting appetite, risk selection, eligibility rules, and pricing factors.

Experience with loss ratio analysis, risk segmentation, predictive modeling inputs, and portfolio management.

Ability to translate underwriting concepts into enterprise data structures, business rules, and ontology definitions.

4. Claims & Loss Expertise

Deep understanding of the claims lifecycle including FNOL (First Notice of Loss), investigation, reserving, settlement, and closure.

Knowledge of indemnity payments, expense payments, reserves, recoveries, subrogation, salvage, and litigation.

Experience analyzing claim frequency, severity, incurred losses, paid losses, and loss development.

Understanding of how loss outcomes connect back to underwriting decisions and exposure characteristics.

Candidates should be comfortable with an on-site presence to support collaboration, team leadership, and cross-functional partnership.

Employee Benefits

We also offer our employees a comprehensive suite of benefits and perks, including:

  • Physical Wellness:Comprehensive medical insurance, dental insurance, and vision insurance; life and disability insurance; fertility benefits; wellness resources; and paid sick time.

  • Mental Wellness:Generous paid time off and holidays; Employee Assistance Program (EAP); and a complimentary Calm app subscription.

  • Financial Wellness:Immediate vesting in a 401(k) plan; Health Savings Account (HSA) and Flexible Spending Account (FSA) options; commuter benefits; and employee discount programs.

  • Family Care:Paid maternity leave and paid paternity leave (including for adoptive parents); legal plan options; and pet insurance coverage.

  • ... and so much more!

This list is not exhaustive of all available benefits. Eligibility and waiting periods may apply to certain offerings. Benefits may vary based on subsidiary entity and geographic location.

Why Join Us:

At Acrisure, we're building more than a business, we're building a community where people can grow, thrive, and make an impact. Our benefits are designed to support every dimension of your life, from your health and finances to your family and future.

Making a lasting impact on the communities it serves, Acrisure has pledged more than $22 million through its partnerships with Corewell Health Helen DeVos Children's Hospital in Grand Rapids, Michigan, UPMC Children's Hospital in Pittsburgh, Pennsylvania and Blythedale Children's Hospital in Valhalla, New York.

Making a lasting impact on the communities it serves, Acrisure has pledged more than $22 million through its partnerships with Corewell Health Helen DeVos Children's Hospital in Grand Rapids, Michigan, UP...


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