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Learning Analytics Jobs in Madison, WI (NOW HIRING)

Varsity Tutors

Business Analytics Tutor

Madison, WI · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Business Analytics tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Machine Learning Tutor

Madison, WI · Remote

$40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Imedica

Affordability Analytics Analyst

Madison, WI · On-site

$90K - $155K/yr

... learning, and celebrates collaboration -- because success is a team sport. It's our mission to be ... Engage with cross-functional teams to identify data needs and ensure alignment on analytics ...

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How much do learning analytics jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for learning analytics in Madison, WI is $39.82, according to ZipRecruiter salary data. Most workers in this role earn between $29.09 and $43.61 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Learning Analytics position, and why are they important?

To thrive in Learning Analytics, you need strong analytical skills, experience with data analysis, and a background in educational research or instructional design, typically supported by a relevant degree. Familiarity with Learning Management Systems (LMS), statistical tools like R or Python, and certifications in data analytics are commonly expected. Excellent communication skills, problem-solving abilities, and a collaborative mindset help professionals convey insights and work effectively with educators and administrators. These skills are essential for interpreting educational data, driving improvements in teaching and learning, and supporting data-driven decisions in academic environments.

What is a Learning Analytics job?

A Learning Analytics job involves collecting, analyzing, and interpreting data related to learners' performance and educational experiences. Professionals in this field use data-driven insights to improve teaching strategies, personalize learning experiences, and enhance institutional decision-making. They work with various analytical tools, machine learning models, and data visualization techniques to identify patterns and trends. This role is common in educational institutions, corporate training programs, and EdTech companies.

What are typical daily responsibilities for someone working in Learning Analytics?

Professionals in Learning Analytics typically spend their days collecting, cleaning, and analyzing educational data to identify patterns that can improve student outcomes and learning processes. They work closely with faculty, instructional designers, and IT teams to generate reports, visualize trends, and advise on data-backed strategies for curriculum improvement. Day-to-day tasks also involve maintaining data integrity, developing dashboards, and communicating findings in accessible ways to stakeholders. Collaboration and ongoing learning are integral, as the field continually evolves with advances in education technology and analytical methods.

What are the 4 types of learning analytics?

Learning analytics can be categorized into four types: descriptive analytics, which analyze past learning data; diagnostic analytics, which identify reasons for learning outcomes; predictive analytics, which forecast future performance; and prescriptive analytics, which recommend actions to improve learning. These types help educators and analysts understand and enhance educational experiences using data analysis tools and techniques.

Is AI replacing data analysts?

Learning Analytics professionals analyze educational data to improve learning outcomes and often use AI tools to automate data processing and generate insights. While AI can handle routine tasks, data analysts are still essential for interpreting complex data, making strategic decisions, and ensuring data quality. AI complements their work but does not fully replace the need for skilled analysts in the field.

Is 40 too late for data science?

Learning Analytics is a field that values skills and experience over age; many professionals transition into data science at 40 or later. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, along with practical experience. Age should not be a barrier to entering data-driven roles if you focus on continuous learning and building a strong portfolio.

What does a learning analyst do?

A learning analyst evaluates educational data to improve learning outcomes by analyzing student performance, engagement, and instructional effectiveness. They use data analysis tools and techniques to identify trends and recommend strategies for curriculum development, often working with learning management systems and reporting software.
What are popular job titles related to Learning Analytics jobs in Madison, WI? For Learning Analytics jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Learning Analytics jobs in Madison, WI look for? The top searched job categories for Learning Analytics jobs in Madison, WI are:
What cities near Madison, WI are hiring for Learning Analytics jobs? Cities near Madison, WI with the most Learning Analytics job openings:
Learning Analytics jobs near you
Infographic showing various Learning Analytics job openings in Madison, WI as of June 2026, with employment types broken down into 64% Full Time, and 36% Part Time. Highlights an 79% In-person, 7% Hybrid, and 14% Remote job distribution, with an average salary of $82,820 per year, or $39.8 per hour.

Data & Analytics Engineer - Marketing Analytics

Robert W Baird & Co

Madison, WI • On-site

Full-time

Posted 12 days ago

Job description

About the Role:

Are you curious about how marketing data turns into insights that drive business decisions? Do you enjoy working handson with data while partnering closely with business stakeholders? Are you looking to deepen your skills in analytics engineering, data modeling, and modern data platforms?

As we continue to grow our data capabilities at Baird, we are seeking a Data & Analytics Engineer (DAE) with a focus on Marketing Analytics. This role is part of our IT Data & Analytics organization and supports marketingfocused use cases such as campaign performance, customer engagement, and channel analytics. The ideal candidate blends data engineering expertise with business curiosity, strong communication skills, and hands-on experience enabling analytics for Marketing stakeholders.

This role is based in Milwaukee, WI and works closely with Marketing, Analytics, Architecture, and Delivery teams.

The Impact You'll Make:

Marketing Analytics & Business Support

  • Partner with Marketing teams and analysts to support analytics needs related to campaigns, customer engagement, and performance reporting.
  • Help translate marketing questions into clear data requirements, datasets, and metrics.
  • Support analytics use cases such as campaign reporting, segmentation, funnel analysis, and customer insights.
  • Build familiarity and trust with Marketing Teams about marketing data sources and how they are used across the organization.

Data Engineering & Data Management

  • Contribute to the design, build, and maintenance of data pipelines that ingest and transform marketing data.
  • Apply data modeling skills (3NF and dimensional) to support analyticsready datasets.
  • Perform data analysis and profiling to understand source data and support quality outcomes.
  • Develop and validate sourcetotarget mappings and transformation logic.
  • Implement and test endtoend data solutions under the guidance of senior engineers.
  • Follow established practices to ensure sensitive data is protected and handled appropriately.

Analytics Enablement & Delivery

  • Support data discovery efforts and help prototype datasets that bring together multiple data sources.
  • Leverage existing tools to enable reporting and visualization for Marketing users.
  • Document datasets and transformations to support usability and adoption.
  • Deliver work incrementally while balancing changing priorities.

Collaboration, Learning & Growth

  • Collaborate with delivery team members, architects, and business partners.
  • Communicate clearly about progress, risks, and dependencies.
  • Learn and apply Baird data standards, tools, and best practices.
  • Seek feedback and coaching from senior Data & Analytics Engineers.
  • Continuously build skills through training, documentation, and handson experience.

What You'll Bring to Baird:

  • 5-7 years of experience delivering data and analytics solutions in a collaborative environment.
  • Experience with data engineering, analytics, or BI development.
  • Strong SQL skills and familiarity with relational data concepts.
  • Experience performing data analysis, profiling, and validation.
  • Ability to work with business partners to understand and support analytics needs.
  • Curiosity, strong problemsolving skills, and a desire to grow technically.

Technical Experience (Representative, Not Exhaustive)

  • Databases / Platforms: SQL Server, Snowflake, Azure SQL Database, Azure Data Lake.
  • Data Integration: SSIS, dbt,Azure Data Factory, or similar tools.
  • Query & Development: SQL, TSQL, Azure Data Studio.
  • BI & Analytics Tools: Power BI, Alteryx, or similar.
  • Data Modeling & Governance: Basic 3NF and dimensional modeling, data mapping, data profiling, data quality concepts.
  • Data Formats: CSV, JSON, XML, Parquet.

Highly Preferred (Marketing Analytics)

  • Exposure to and experience with marketing or customer data (campaigns, digital engagement, CRM, or customer interaction data).
  • Interest in marketing measurement concepts such as attribution, segmentation, or funnels.
  • Experience working in a regulated or datasensitive environment.

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Baird is committed to diversity and provides employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, pregnancy, citizenship, national origin, age, disability, military service, veteran status, sexual orientation, gender identity or expression, genetic information, or any other status protected by law.

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