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Hr Data Analytics Jobs in Wisconsin (NOW HIRING)

ULINE

Human Resources Analyst

Kenosha, WI

Analyze Human Resources (HR) data to identify workforce trends and support recruiting, retention and workforce planning. * Create reports and deliver insights that help leaders make informed ...

ULINE

Human Resources Analyst

Pleasant Prairie, WI · On-site

Analyze Human Resources (HR) data to identify workforce trends and support recruiting, retention and workforce planning. * Create reports and deliver insights that help leaders make informed ...

ULINE

Human Resources Analyst

Milwaukee, WI

Analyze Human Resources (HR) data to identify workforce trends and support recruiting, retention and workforce planning. * Create reports and deliver insights that help leaders make informed ...

ULINE

Human Resources Analyst

Pleasant Prairie, WI

Analyze Human Resources (HR) data to identify workforce trends and support recruiting, retention and workforce planning. * Create reports and deliver insights that help leaders make informed ...

BCforward

Data Analyst II

Waukesha, WI · On-site

$21.60/hr

Data Analyst II Waukesha, WI, USA, 53188 $21.60/hr on w2 12/12/2016 to 06/16/2017 Global Services role supporting data analysis on trapped parts within the GEHC network. The primary goal of this will ...

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All JobsHr Data Analytics JobsHr Data Analytics Jobs in Wisconsin

Hr Data Analytics information

See Wisconsin salary details

$46.4K

$166.6K

$245.8K

How much do hr data analytics jobs pay per year?

As of Aug 10, 2026, the average yearly pay for hr data analytics in Wisconsin is $166,561.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,700.00 and $171,600.00 per year, depending on experience, location, and employer.

Can HR become a data analyst?

HR professionals can transition into data analyst roles by developing skills in data analysis, statistics, and tools like Excel, SQL, or Tableau. Gaining experience with data-driven decision-making and obtaining relevant certifications can facilitate this career shift.

What is the difference between Hr Data Analytics vs HR Analyst?

AspectHr Data AnalyticsHR Analyst
Primary FocusAnalyzing HR data to identify trends and insightsInterpreting HR data to support HR functions and decision-making
Skills RequiredData analysis, statistical tools, HR knowledgeHR policies, data interpretation, communication skills
Tools UsedExcel, SQL, data visualization softwareExcel, HRIS systems, reporting tools
Work EnvironmentData-driven, analytics teams, HR departmentsHR departments, business units

While both roles involve working with HR data, Hr Data Analytics primarily focuses on analyzing large datasets to uncover trends and insights, often requiring advanced data skills. HR Analysts interpret data to support HR functions like recruitment and employee relations. The roles overlap but differ in scope and technical depth.

What are the key skills and qualifications needed to thrive as an HR Data Analytics professional, and why are they important?

To thrive as an HR Data Analytics professional, you need strong analytical skills, a background in human resources or data science, and knowledge of statistical methods. Familiarity with HRIS platforms, data visualization tools like Tableau or Power BI, and proficiency in Excel or programming languages such as Python or R are typically required. Critical thinking, attention to detail, and effective communication help you translate complex data into actionable HR insights. These skills are essential for driving data-informed decision-making, optimizing workforce strategies, and demonstrating HR's value to organizational goals.

Does HR Data Analytics pay well?

HR Data Analytics professionals typically earn competitive salaries that reflect their specialized skills in data analysis, HR systems, and statistical tools. Salaries vary based on experience, location, and industry, with many roles offering additional benefits and opportunities for advancement.

What is HR Data Analytics?

HR Data Analytics, also known as Human Resources Analytics or People Analytics, is the process of collecting, analyzing, and interpreting data related to an organization's workforce. It helps HR professionals make data-driven decisions about hiring, employee performance, retention, and development. By leveraging various metrics and tools, HR Data Analytics aims to improve organizational effectiveness and employee satisfaction. This approach enables companies to identify trends, forecast workforce needs, and optimize HR strategies.

How does an HR Data Analytics professional typically collaborate with other departments within an organization?

HR Data Analytics professionals frequently work cross-functionally, partnering with departments such as IT, finance, and operations to gather relevant data and extract actionable insights. They collaborate closely with HR business partners and leadership to align analytics initiatives with organizational goals, often participating in meetings to present findings or discuss workforce trends. Effective communication and teamwork are essential, as HR data analysts must translate complex data into strategies that support talent management, diversity initiatives, and overall business performance.

Is HR Data Analytics a good job?

HR Data Analytics is a growing field that involves analyzing employee data to improve HR strategies and decision-making. It requires skills in data analysis tools like Excel, SQL, or Python, and often benefits from certifications in HR or data analytics. The role offers opportunities for career advancement and is in demand across various industries.
What are popular job titles related to Hr Data Analytics jobs in Wisconsin? For Hr Data Analytics jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Hr Data Analytics jobs in Wisconsin look for? The top searched job categories for Hr Data Analytics jobs in Wisconsin are:
Hr Data Analytics jobs near you
Infographic showing various Hr Data Analytics job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $166,561 per year, or $80.1 per hour.

Principal Data Analyst

Continuus Technologies LLC

Germantown, WI • On-site

Full-time

Re-posted 2 days ago

Job description

Role OverviewThe Principal Data Analyst is a strategic analytics leader and subject-matter expert who shapes how data is used across the organization. This role leads the most complex, high-impact analyses, defines analytical standards, and partners with executive leadership to influence long-term business strategy. The Principal Data Analyst operates with broad autonomy and serves as a mentor and thought leader across the analytics community.Key ResponsibilitiesLead enterprise-level, high-impact analyses that inform strategic decisionsDefine and govern company-wide KPIs, metrics, and analytical frameworksTranslate ambiguous, complex business problems into structured analytical approachesInfluence executive decision-making through clear, compelling data storytellingPartner with senior leadership to shape analytics strategy and prioritiesSet standards for analytical rigor, experimentation, and data interpretationMentor Staff and Senior Analysts and elevate analytical excellence across teamsDrive improvements in data quality, metric consistency, and governanceIdentify emerging trends, risks, and opportunities proactivelyQualificationsBachelor's degree in Data Analytics, Statistics, Economics, Business, or related field (or equivalent experience)10+ years of experience in analytics or data-focused rolesExpert-level SQL and advanced analytical modeling skillsExtensive experience with BI and visualization platforms (Tableau, Power BI, Looker, etc.)Strong statistical reasoning and business acumenProven ability to influence executive stakeholders through insightsPreferred ExperienceAdvanced proficiency in Python or R for analysisExperience designing experimentation or causal analysis frameworksFamiliarity with data engineering and modern data architecturesDomain expertise (e.g., product, finance, HR, operations, growth analytics)Experience shaping analytics strategy without direct people management