Job Description

Roles & Responsibilities

Key Responsibilities

Data Management & Advanced Analysis

Data Collection & Preparation: Collate, clean, filter, and organize large datasets from various sources such as databases, spreadsheets, and external APIs. Use existing R scripts and support coding, analyzing, and collating survey data.

Data Quality Assurance: Conduct thorough validation and consistency checks, resolving discrepancies to maintain high data integrity.

Statistical Analysis: Perform exploratory, descriptive, inferential, and multivariate statistical analyses. Apply appropriate tests to establish the significance of results and provide evidence-based conclusions.

Visualization, Reporting & Presentation

Develop clear, impactful dashboards, charts, and reports using Tableau, Power BI, or Excel, presenting complex data in a simplified, compelling way.

Prepare and deliver presentations that effectively communicate data insights, trends, and recommendations to both technical and non-technical audiences.

Prepare regular and ad-hoc reports tailored to diverse stakeholders, ensuring outputs are both insightful and accessible.

Cross-Functional Collaboration

Partner closely with Culture Coaches, Customer Success, Marketing, Sales, and the Lists team to ensure data quality supports business needs and enhances products.

Assist senior team members on strategic or ad-hoc projects, delivering data-driven support that influences key decisions.

Research & Continuous Improvement

Research and identify emerging data trends relevant to workplace culture, exploring new ways Great Place to Work can analyze and present data for impact.

Recommend enhancements to data analysis methods, tools, and workflows to drive efficiency and insight.

Problem-Solving & Optimization

Use data creatively to help solve business challenges. Translate complex problems into analytical tasks, identify patterns, and propose actionable solutions.

Data Privacy & Compliance

Maintain strict confidentiality and handle data responsibly, ensuring compliance with data privacy regulations and internal governance standards.

Professional Growth

Stay current with industry trends, tools, and techniques in data analytics, visualization, and machine learning. Continually develop expertise in statistical analysis and advanced data methods.

Requirements

Qualifications & Experience

Education: Bachelor’s degree (or higher) in a quantitative field such as Statistics, Computer Science, Economics, Sociology, or Quantitative Psychology.

Experience: Minimum 5 years in a dedicated data analysis role, with demonstrated experience in:

Cleaning, transforming, and merging large datasets from multiple sources.

Conducting descriptive, inferential, and multivariate statistical analyses.

Developing advanced dashboards and visualizations.

Presenting complex data and insights clearly in both written reports and live presentations.

Technical Skills

Proficiency in statistical analysis tools such as R, Python, SPSS, or STATA.

Strong SQL skills for querying and managing relational databases.

Advanced Excel, including pivot tables and complex formulas.

Skilled in data visualization platforms like Tableau or Power BI.

Core Competencies

Analytical Mindset: Ability to distill complex datasets into clear, actionable insights.

Attention to Detail: Commitment to data accuracy, validation, and high standards.

Communication: Strong verbal and written skills to present complex findings in a simple, impactful manner, including confident delivery of presentations.

Collaboration: Effective team player who works well with remote and cross-functional teams.

Organization & Time Management: Capable of managing multiple priorities and meeting tight deadlines.

Adaptability: Quickly learns new tools and adjusts to evolving business needs.

Solution-Focused: Uses data creatively to identify opportunities and solve problems.

The scope of this role may grow or evolve over time in alignment with the organization’s strategic priorities and business needs.

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