Data Analytics & Experimentation Lead

Shrive Technologies LLC; Antonia (LA); On-site; USD 110,000 - 140,000; Full time

Job summary

Shrive Technologies LLC seeks a data analytics expert to design, implement, and evaluate A/B and multivariate experiments aimed at optimizing member acquisition, engagement, and retention. The role requires applying regression, hypothesis testing, predictive modeling, segmentation, and causal inference to drive actionable business recommendations.

You will analyze large datasets, collaborate with product and marketing, and develop dashboards and reports that communicate key insights and metrics

Qualifications

• Strong expertise in statistical methodologies, experimental design, and hypothesis testing.
• Proven experience leading end-to-end A/B testing and experimentation programs.
• Proficiency in SQL, Python, R, or similar analytical tools.
• Experience supporting customer/member retention, loyalty, engagement, or lifecycle management initiatives.
• Excellent analytical, problem-solving, and communication skills.

Responsibilities

• Design, implement, and evaluate A/B and multivariate experiments to optimize member acquisition, engagement, and retention strategies.
• Apply advanced statistical methods, including regression analysis, hypothesis testing, predictive modeling, segmentation, and causal inference.
• Analyze large and complex datasets to identify trends, opportunities, and key drivers of member behavior.
• Translate analytical insights into actionable business recommendations.
• Collaborate with product, marketing, and business stakeholders to define success metrics and measurement frameworks.
• Develop dashboards, reports, and presentations to effectively communicate findings and recommendations.

Skills

A/B testing

Experimental design

Statistical methods

Data analysis

Tools

SQL

Python

R

Job description

Shrive Technologies LLC seeks a data analytics expert to design, implement, and evaluate A/B and multivariate experiments aimed at optimizing member acquisition, engagement, and retention. The role requires applying regression, hypothesis testing, predictive modeling, segmentation, and causal inference to drive actionable business recommendations.

You will analyze large datasets, collaborate with product and marketing, and develop dashboards and reports that communicate key insights and metrics