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Zurich NA Learning Measurement Consultant in Schaumburg, Illinois

Learning Measurement Consultant

Description

Zurich North America is currently looking for a Learning Measurement Consultant for Underwriting University in the Measurement, Sustainment, and Technology group to work out of our North American Headquarters in Schaumburg, Illinois, or virtually.

The Learning Measurement Consultant is a new part of the recently created Zurich Underwriting University and is aligned with Zurich’s Technical Underwriting organization to deliver industry, product, and process training to Zurich’s Technical Underwriting staff.

In this new role, your experience with aggregating, analyzing, and presenting learning and Human Resource data will be critical to Underwriting University’s success. You will be vital in establishing measurement strategies, developing and executing plans, and keeping ahead of trends in learning measurement.

Additional responsibilities include:

  • Establishing KPIs with business partners

  • Sourcing and aggregating data

  • Developing analytic models and tools

  • Performing strategic analysis (segmentation, correlation, multiple regression, trend analysis, behavioral analysis, predictive modeling, etc.)

  • Generating data-driven insights through partnership and collaboration with Underwriting University, its business partners, and functional experts.

Basic Qualifications:

  • Bachelor’s Degree in Business Administration, Economics, Finance, Mathematics/Statistics, or Data Analytics and 7 or more years of experience in the Data Analysis areaOR

  • High School Diploma or Equivalent and 9 or more years of experience in the Data Analysis areaOR

  • Zurich Certified Insurance Apprentice including an Associate Degree in Business Administration or Economics or Finance or Mathematics/Statistics or Data Analytics and 7 or more years of experience in the Data Analysis areaAND

  • Seven or more years working in an Analytics environment

  • Knowledge of HR data and Workforce Analytics

Preferred Qualifications:

  • Master’s Degree with a statistical or quantitative background

  • People and/or Learning analytics experience

  • Experience with data lakes and data mining

  • Strong problem-solving skills

  • Strong communication skills

  • Advanced Microsoft Excel, Access and PowerPoint skills

  • Familiarity with visual analyzers (e.g., Power BI, Tableau)

  • Knowledge of SAP and of interfaces between modules in SAP and underlying business processes producing the data output

  • Modeling expertise using advanced statistical techniques to address business problems via regression, segmentation, decision tree, time series, and other multivariate analysis.

Imagine working for a company that truly cares about their employees, customers, stakeholders, and communities they serve.

Imagine working for a values-driven organization that has the ambition and desire to be the best global insurance provider in the world.

Zurich is that place where 55,000 employees across approximately 200 countries and territories are all focused on helping people and helping companies protect what is truly most important to them. We are a values-driven organization that takes pride in the work that we do every day and we have the ambition to be the best global insurer in the world.

EOE disability/vets

Zurich does not accept unsolicited resumes from search firms or employment agencies. Any unsolicited resume will become the property of Zurich American Insurance. If you are a preferred vendor, please use our Recruiting Agency Portal for resume submission.

Primary Location: United States-Illinois-Schaumburg

Other Locations: United States-Virtual

Schedule Full-time

Travel Yes, 10 % of the Time

Relocation Available No

Job Posting 03/23/20

Unposting Date Ongoing

Req ID: 200002CX

It is the Policy of Zurich in North America, as an equal opportunity employer, to attract and retain the best-qualified individuals available, without regard to race/ethnicity, color, religion, gender expression, genetic information, national origin, sex, gender identity, sexual orientation, marital status, age, disability or protected veteran status.

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