Data Analyst II

The Data Analyst II on the Appcast Data & Insights Team works at the convergence of data, recruiting strategy, and product insights. This role focuses on turning complex recruitment marketing data into clear, actionable recommendations and compelling narratives. Data Analyst II operates with a high degree of independence and is responsible for delivering analyses, dashboards, and client-facing insights end-to-end. 

Data Analyst II supports Account Managers, Product teams, and internal stakeholders to understand performance trends, identify key drivers, and communicate data into meaningful customer context that supports client strategy. This includes not only reporting on what is happening but also helping explain why it matters and how it informs strategic decisions. They also lead or own components of client business reviews, build dashboards and reporting tools, and translate labor market and performance data into clear narrative-driven insights. This role requires strong analytical skills, comfort working with large datasets, and the ability to communicate complex findings clearly to both technical and non-technical audiences. 

Job Responsibilities

• Analyze Performance Data and Identify Insights: Work with large and complex datasets to identify trends, performance gaps, and opportunities for optimization. Apply independent judgement to interpret findings and deliver actionable insights that support client strategies and internal decision-making. 
• Create Client-Facing Insights and Business Reviews: Lead the development of analyses and visualizations for client presentations (e.g., QBRs, custom reports). Craft clear, compelling narratives that connect data to business outcomes, helping clients understand performance trends, labor market dynamics, and strategic opportunities. 
• Build and Maintain Dashboards and Reporting: Design, build, and own dashboards and automated reporting tools using platforms such as Tableau or Streamlit. Ensure reporting is accurate, scalable, and aligned to support decision-making. 
• Collaborate Across Teams: Partner closely with Account Management and Product teams to translate data into clear, actionable insights. Provide analytical direction and input into product initiatives, internal tools, and cross-team projects. 
• Improve Analytics and Reporting Processes: Proactively identify and implement improvements to enhance data workflows, reporting efficiency, and automation. Contribute to advancing the team’s analytical capabilities using tools such as SQL, Python, or R. 
• Manage Analytical Projects and Documentation: Track projects and maintain documentation using systems such as Salesforce, JIRA, GitHub, and Confluence to ensure transparency and reproducibility. Independently manage moderately ambiguous analytical requests from intake through delivery, applying structured problem-solving and sound judgment to deliver clear, reliable outputs.