Product Analyst

EPCVIP•Calabasas, CA

About The Position

EPCVIP is hiring a Product Analyst to run the day-to-day execution of funnel and acquisition experiments within Product Operations. At EPCVIP, we run a high-volume consumer-lending marketplace that connects people with financial offers through a network of partners. We continuously experiment to improve conversion, lead quality, and marketplace performance. In this role, you will own assigned initiatives from hypothesis and implementation through analysis and recommendation. This is an execution and analysis role for someone early in their product career who already works comfortably with AI tools. You will use Claude Code, our internal skill library, and data warehouse integrations to develop and verify queries, structure analyses, and produce clear readouts. The tools accelerate the work, but you remain responsible for validating the logic, data, and conclusions.

Requirements

Bachelor’s degree in Business, Economics, Analytics, Statistics, Information Systems, Computer Science, or a related quantitative field, or equivalent practical experience.
1–2 years of experience in product analytics, data analytics, product operations, or a related field; new grads with strong internship or project experience are welcome to apply.
Proficiency in SQL and Python for querying, analyzing, and validating data.
Working knowledge of A/B testing, including hypothesis design, sample sizing, statistical significance, peeking, and sample-ratio mismatch.
Ability to turn an ambiguous product question, funnel metric, or experiment result into a structured analysis and clear recommendation.
Strong ownership and execution, with the ability to move initiatives forward, maintain clear documentation, and escalate blockers early.
Strong analytical judgment and curiosity, with the discipline to investigate unexpected results and verify conclusions.
Experience using tools such as Claude Code, Cursor, and ChatGPT.

Nice To Haves

Exposure to lead generation, performance marketing, affiliate networks, funnel or conversion-rate optimization, or adtech.
Experience with digital analytics tools such as GA4, Amplitude, Mixpanel, or similar.
Experience building something practical with AI tooling, such as a script, agent, workflow, or small internal tool.

Responsibilities

Define the hypothesis, success metrics, guardrails, and decision criteria for assigned initiatives.
Estimate expected lift, required sample size, statistical power, and test duration before committing to a build.
Use historical and segment-level data to evaluate opportunities and support prioritization.
Contribute ideas based on user behavior, competitor funnels, mock-ups, and performance trends.
Run assigned lead-acquisition experiments from approved concept through final decision.
Coordinate implementation with Design and Engineering, complete QA, launch the test, and monitor live performance.
Analyze results, evaluate statistical significance, and document a clear recommendation.
Maintain experiment tickets, documentation, timelines, and status visibility.
Surface tracking gaps, sample-ratio mismatch, unexpected metric movement, and other anomalies early.
Investigate funnel performance, conversion trends, revenue movements, and stakeholder questions.
Frame analytical questions, segment the data, and conduct analyses using SQL, Python, and AI tooling.
Validate query logic, data quality, and unexpected findings before reaching a conclusion.
Produce concise, shareable readouts with clear findings, limitations, recommendations, and next steps.
Partner with BI when work requires deeper data modeling or more extensive analysis.
Keep assigned initiatives moving across Product, Engineering, Design, QA, and BI.
Work with your manager on prioritization, interpretation, and key decisions.
Translate findings into clear recommendations for technical and non-technical audiences.
Escalate blockers, risks, and uncertainty early.