Product Manager, Data Products

Location:

Remote - Headquarters located in Burlington, MA

Remote

Exempt

Chief Product Officer

Product

Base salary range: $134,000 - $145,000

(This role is compensated as base salary plus a company discretionary bonus. The bonus is determined by company performance and is not guaranteed.)

Prendio's platform runs procurement and payments for biotech companies. That gives us a distinctive view of how life sciences organizations buy — what they purchase, from which suppliers, at what price, and how all of that shifts over time. We have solid foundational reporting on top of that today. What we have not done yet is turn it into products.

That is what this role is for. You will own data products at Prendio: figure out what our data can tell customers that nobody else can, turn those insights into products people will pay for, and take them to market. This is close to a blank sheet. The business case is already identified and the revenue behind it is significant. You are being brought in to convert that into real products, not to maintain reporting that already exists.

You will start on the biotech side of the business and expand into the supplier side as the area matures. You will work directly with engineering and the data team, alongside the owner of the business line, and you will own commercialization and go-to-market. This is an individual contributor role with clear ownership of the area.

• Define what we build, who it is for, and why. Identify which proprietary and non-proprietary data assets carry commercial value and determine how they get packaged into products.
• Build the roadmap and sequence it around where we have the best chance to win.

• Run discovery with customers to validate what is worth building before we build it.
• Own packaging, pricing, and go-to-market in partnership with the business line owner, sales, and marketing.
• Prove commercial value. These products are expected to generate measurable revenue, not just usage.

• Partner with analysts, architects, and engineering to translate opportunities into concrete requirements: datasets, calculations, and functionality.
• Prototype your own concepts. We are tool-agnostic — there are plenty of ways to do this now — but we expect you to be able to stand something up yourself and pressure-test an idea before it goes into the roadmap.

• Understand what we can and cannot do with the data we hold: data rights, privacy, contractual restrictions, and regulatory obligations.
• Surface those constraints early and design around them rather than discovering them at launch.
• Project manage delivery with engineering. Keep priorities clear and the work moving.
• Own the underlying capabilities your products depend on. Where a data product needs platform, reporting, or infrastructure work to happen first, you drive that to completion with the teams and owners responsible for it.
• Bring the customer and commercial context into the room so the team is building the right thing, not just building.

• You will start by proving out the first data products on the biotech side of the business, then expand into the supplier side as the area matures.
• The near-term focus is depth of ownership as an individual contributor rather than building a team. As data products grow into a business in their own right, the role is positioned to grow with it.

• We know which of our data assets are commercially viable, and which are not, because you have tested the hypotheses rather than argued them.
• At least one data product is in market, priced, and generating revenue.
• There is a roadmap the business believes in, sequenced by where the opportunity is real.
• Engineering and the data team know what they are building and why, and the work is moving on a predictable cadence.
• Compliance and data-rights questions get answered early in the process, not at launch.

• Learn the data. Understand what we hold, where it comes from, and…