Wilmington, DE, United States
1 day ago
Workforce Planning Data Analyst - Sr. Associate

As a Workforce Planning Data Analyst - Sr. Associate in the Talent Data Strategy and Insights team, you will aim to create data-driven experiences that enhance the employee journey. We are seeking an experienced professional to join our team, who can skillfully manage data, craft compelling data narratives, and collaborate with stakeholders to identify challenges and develop impactful solutions. The ideal candidate is adept at understanding complex business issues and transforming them into data-driven solutions. You should be equally comfortable analyzing intricate data sets, developing dashboards, and brainstorming solutions to underlying business problems.

Key Responsibilities:

Develop engaging data experiences, dashboards, and reports that encourage users to explore and learn more. Be resourceful and creative in sourcing and analyzing data. Serve as the expert on internal people-related data, providing data-driven solutions to stakeholders' challenges. Communicate actionable insights and analytical methods to non-technical partners. Automate tasks and enhance efficiencies in traditional data processes. Collaborate with multiple teams and effectively navigate unstructured, ambiguous environments. Lead end-to-end projects independently while managing stakeholder expectations. Mentor peers and partners to enhance their data fluency and analytical skills.

Minimum Qualifications:

3+ years of professional experience as an analyst in a business intelligence role. Proven success across the analytics project lifecycle, including solution design, data extraction and transformation, descriptive data analysis, and data visualization. Advanced proficiency in data analysis and visualization tools (Excel, Tableau, Alteryx, and Python). Strong verbal and written communication skills with both technical and non-technical colleagues and senior stakeholders.

Preferred Qualifications:

Experience with people analytics projects. Familiarity with statistics and data science techniques.
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