Sr Data Analyst, Talent Acquisition Operations

5+ years of experience in Recruiting Operations, People Operations, or Analytics team with a demonstrated track record of operational excellence and innovation. 3+ years in a stakeholder management and managing large data sets Experience in data analytics (4+ years of related experience) Fluent in SQL and familiar with data warehouses such as Redshift, BigQuery, or Snowflake An expert with Excel/GSheets and data visualization tools such as Sigma, Tableau or similar software Familiar with recruiting software such as Greenhouse, Gem, LinkedIn etc Experience with leading and delivering data related projects An excellent communicator (verbal and written) with interpersonal skills to develop and communicate clear, comprehensive analyzes and influence stakeholders

Build the future of the recruiting analytical infrastructure by understanding our current tech stack and build a data warehouse which will enable you to perform queries and analysis between multiple sources Drive some of the most critical decisions in both the recruiting and the business in how we calculate key performance metrics and how we share our data to our business partners Leverage a data first approach to identify critical business trends to deliver both insights and specific actionable recommendations to the business Build and maintain critical dashboards, reports and presentations that enable key leaders to understand, interpret and make decisions Create predictive models and trend analysis for the recruitment team by understanding historical data to predict future outcomes so that the recruiting leaders can make more informed decisions and for strategic planning purposes Create audits to identify opportunities for training and improvements within the recruitment end to end process Focus on quantitative and qualitative data analytics to find insights and meaningful business outcomes Tell the story from the insights through dashboards, visualizations and presentations Monitor and validate data ensuring high-quality information is collected and accurately stored. Help to continually improve data management methods and systems. Proactively suggest opportunities to avoid problems and anticipate future data needs.