Overview AvePoint is on the lookout for a highly motivated People Analytics Intern for 2024, who brings a passion for utilizing data to inform and drive strategic business and workforce decisions. The People Analytics team is a critical driver in leveraging data-driven insights to influence key strategic areas including workforce planning, optimizing HR practices, employee retention strategies, and boosting sales efficiency. This internship offers a unique opportunity to contribute to pivotal projects that align with and directly influence our strategic objectives for the year.
This year's internship will center around this primary initiative to ensure AvePoint's continued success and growth:
Building a Predictive Model for Employee Churn: This project focuses on developing a sophisticated predictive analytics model aimed at identifying potential employee turnover before it happens. By analyzing patterns and predictors of churn, this initiative seeks to enable proactive retention strategies, ultimately helping AvePoint to retain its valued talent.
In This Internship, You Will Be Tasked With
Engaging with senior stakeholders across HR and Sales departments to gather and document critical business questions focused on reducing employee churn and enhancing sales forecasting
Conducting comprehensive research and analysis to identify patterns and opportunities for improvement in employee retention strategies and sales pipeline efficiency.
Developing data-driven insights and recommendations to support HR and Sales decision-making, using advanced analytics techniques.
Communicating findings and recommendations to stakeholders through detailed presentations and reports.
Implementing your findings into a PowerBI dashboard for ongoing monitoring and decision support, aiming to integrate these insights into AvePoint's strategic planning.
Working collaboratively with the People Team, Sales, and other stakeholders to implement recommendations and drive meaningful change.
Skills And Qualifications Analytical skills, specifically:
Exploratory Data Analysis , data cleaning, extracting summary statistics, univariate analysis (Histogram, Frequency Distribution/Histogram), and advanced statistical techniques (ECDF, Correlation Table, etc.).
Technology proficiency is beneficial but not required: PowerBI, Python, R, SQL, Visual Studio Code Editor, Github, SQL Server
Knowledge of Linear and Logistic Regression, additional machine learning techniques is a plus
HR and Sales Technology familiarity is a plus but not required: