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Senior Product Data Analyst (remote from GMT-7 to GMT+4 timezones)

Serbia · remote · Salary not listed

Role overview

About Collectly

Collectly is a fast-growing healthcare technology company transforming revenue cycle management (RCM) through AI-driven automation. Millions of patients navigate inefficient billing systems every day, while providers face delayed payments, rising administrative burden, and operational complexity.

Collectly applies artificial intelligence to automate workflows, accelerate cash flow, and modernize the patient financial experience; enabling healthcare organizations to operate more efficiently and focus on delivering care.

There could not be a hotter space to play in. Healthcare is a $4.9T industry and is adopting AI technology at 2.2x the rate of the rest of the economy. RCM is at the heart of this transformation as it has a clear and demonstrable ROI to our customers.

About the role

We’re hiring a Senior Product Data Analyst to own how customers and our own teams see product performance. You will work both on our pre-service products (visit cost estimates, eligibility and benefits, patient support voice agent) and post-service (patient billing, revenue cycle metrics). You’ll
own the dashboards for these products, provide visibility into our product performance, and use the data to find product gaps.

You’ll build customer-facing metrics yourself, mostly with AI tools like Claude Code. This is a product role more than an infrastructure one: we want your time going into how each product behaves and what customers run into, not into maintaining pipelines.

We are a hybrid company, partly based in Santa Monica, USA and partly remote, spread out around the United States & Europe.

Key responsibilities

In this role you will

Own the dashboards that product and customer teams work from, across most of our products.
Turn complaints and open questions into defined metrics, and track them over time.
Catch product issues in the data before they become escalations.
Work with the founder, product managers, engineers, and customer success to decide what to measure, and explain why a number moved.