Hiring Manager: VP of People Science

Responsibilities

• Execute analytics projects that provide the People Scientist team with the insights they need to delight our customers
• Work with People Scientists and Engineering teams to ensure data pipelines and datasets are built to scale from large-scale datasets to help support on-demand research and analytics
• Lead various core analytics projects, assigned by the VP of People Science, that are critical to ensuring EngageRocket’s platform provides the best insights for customers
• Support the People Science team in the development of new programs by providing analysis to validate the approaches & measures
• Research and answer questions from EngageRocket customers and internal staff about our analytics capabilities
• Execute cross-client research projects under the direction of the VP of People Science
• Initiate, document and process-improve the EngageRocket People Science Analytics toolkit, using basic program coding and script-writing to automate and streamline routine analytics
• Experience giving care and attention to the efficient delivery of complex analytics projects -- this is important as we scale and grow to serve an ever-expanding list of customers

Basic Qualifications

• Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, Engineering, or related discipline
• 3+ years experience analyzing data and building mathematical models
• Experience conducting statistical analyses in R or python and managing data using SQL or equivalent
• Ability to understand complex concepts, then break them down and explain why they matter in simple terms
• Strong communications skills: adept at queries, report writing and presenting findings
• Positive, authentic, connected, and transformative mindset about work
• Detail-oriented, independent, and quality-obsessed tendencies

Preferred Qualifications

• Post-graduate degree in related discipline
• 3+ years experience consulting in the employee engagement industry, or applying statistics, survey design, and I-O/OD theories in organisational settings
• Experience giving good feedback to people seeking your advice on complex research problems
• Demonstrated examples of identifying best approach and running statistical analyses (Correlations, linear & logistic regressions, SEM, multilevel modeling, etc.) to examine relationships between predictors and outcomes
• Knowledge of best practices in data structure and management