Senior Data Science Analyst

About Harver

Harver is the industry leading hiring solution helping organizations optimize their talent decisions. Rooted in over 35 years of rich data insights, the company’s portfolio of solutions enables organizations to make the best talent decisions across the entire employee lifecycle. Having processed over 100 million candidates, Harver provides trusted, flexible, and adaptable offerings making hiring better, faster, and fundamentally more fair. More than 1,300 customers trust Harver to help put purpose to work.    

At Harver, we are:  

• Transparent: We believe in fostering an open, honest, and accountable environment where information flows freely and clearly.
• Collaborative: We embrace the power of collaboration and recognize that every individual brings unique strengths to the table.
• Curious: We embrace curiosity as a driving force for continuous learning and innovation.

Job Overview:

We're seeking a Senior Data Analyst to join our Data Science team, where you'll play a critical role in demonstrating the business value of our talent assessment solutions to Fortune 500 clients. You'll execute predictive validity studies and outcome analyses that prove ROI for major enterprise clients across various industries. 

This role focuses on the end-to-end execution of outcome studies—from client data intake and matching through analysis delivery. You'll work with established frameworks and tools while applying strong analytical thinking to translate complex data into compelling client insights. 

In this role you get to: 

Client Data Management 

• Intake and validate client outcome data (performance, retention, hiring funnel, demographic,  productivity metrics) 

• Clean and standardize diverse data formats from enterprise HRIS and ATS systems 

• Match client candidate records with Harver assessment data with high accuracy 

• Troubleshoot data quality issues and communicate data requirements to clients 

• Document data specifications and maintain data integrity throughout analysis lifecycle 

Predictive Validity & Outcome Analysis 

• Execute concurrent & predictive validity studies using established statistical frameworks 

• Apply machine learning models (Random Forest, XGBoost) to predict performance and attrition outcomes from assessment data 

• Conduct ROI analyses demonstrating business impact (cost savings, quality of hire improvements) 

• Perform disparate impact analyses to ensure assessment fairness 

• Generate client-ready reports and visualizations communicating technical findings to business stakeholders 

Technical & Collaboration 

• Query and analyze data using Looker and SQL from internal databases 

• Collaborate with Data Scientists on methodology refinement and framework improvements 

• Support Client Success teams with technical questions and ad-hoc analyses 

• Maintain analysis documentation and contribute to team knowledge base 

• Present findings to internal stakeholders and client-facing teams 

• Strategic collaboration with People Science team to improve efficiency and effectiveness of solutions 

• Identify custom solutions based on client escalations and build into repeatable process for similar issues in the future 

We’re looking for people who have:  

• 5+ years of experience in data analysis, preferably in HR tech, people analytics, or consulting 

• Strong proficiency in data cleaning, transformation, and quality assurance with complicated real-world datasets 

• Solid statistical foundation (regression, hypothesis testing, correlation analysis, model evaluation metrics) 

• Experience applying machine learning models as a user (model scoring, interpretation, validation) 

• Proficiency in both Python and R for data analysis (pandas, dplyr, data visualization libraries)