Product Operations & Data Analytics Intern

EPCVIP is a technology company specializing in lead generation within the Financial Services Industry. Our expertise in PPC traffic, search engine, display and email marketing has propelled us to the forefront of the lead generation industry. We have developed a customizable optimization platform, allowing us to yield the highest EPCs in the industry. The key to our success is attributed to our talented employees and superior proprietary technology. We are looking for a detail-oriented and analytical Product Operations & Data Analytics Intern to support our Product Operations team. This internship offers hands-on experience in a fast-paced, innovation-driven environment where you'll contribute to data analysis, workflow optimization, and experimentation initiatives that drive business performance.

Internship description:

Analyze operational and performance data to identify trends and actionable insights Support experimentation initiatives, including tracking, reporting, and rollout coordination Assist in optimizing workflows and improving operational processes Contribute to AI-driven automation and process improvement projects Maintain and update internal tools, systems, and documentation Support QA testing and ensure accuracy of operational outputs Collaborate with Product, Engineering, and Data teams to identify and solve operational challenges Currently pursuing or recently completed a degree in Business, Economics, Analytics, Statistics, Information Systems, or a related field Strong analytical and problem-solving skills Proficiency in Excel or Google Sheets Excellent communication and organizational skills Strong attention to detail and ability to manage multiple tasks Interest in data, operations, and process improvement Exposure to automation tools (Claude Code) or AI-driven workflows Preferred

• Experience with analytics tools (e.g., SQL, Tableau, Looker, Python)
• Familiarity with A/B testing or experimentation frameworks
• Previous internship or project experience in analytics or operations