About Us

Applecart is the leading technology company that C-suites rely on to reach business-critical decision makers. The most important decisions are made by the hardest people to reach and influence. Historically, C-suite leaders have lacked the tools to reach the stakeholders who matter most to their business. The C-suites of hundreds of Fortune 500 companies, major agencies, trade associations, nonprofits, and governments use Applecart to put their best content in front of business-critical decision makers and those they trust — from policymakers and investors to CEOs, key employees, members of the media and more. Decision makers are informed by what they read, learn from advisors, hear from colleagues, and discuss with family and friends. To break through to them, you must reach them through the only channel that really moves them: those they know and trust. Applecart’s platform uses publicly available data to map billions of social relationships between nearly every American adult and enable clients to deliver content directly to decision makers and those who matter most to them.

We are hiring a Senior Product Manager, Decision Maker Networks Platform in our New York office.

About the Role

Applecart's Decision Maker Networks are the foundation of everything we deliver and the value our platform drives. Our proprietary models and scoring algorithms map the relationships between Decision Makers and the people they trust, and the depth and differentiation of those networks determines the precision of every audience we deliver to Fortune 50 companies, major PE firms and leading trade associations.

We are hiring a Senior Product Manager to own the Decision Maker Networks platform — the harness, architecture and tooling that Data Scientists at Applecart build within. You will own the rails our scoring models run on, the bar they must clear, and the levers the rest of the company uses to tune them. The ideal candidate pairs strong product judgment with genuine fluency in algorithmic products, and is as comfortable defining how Networks should adapt to the unique strategic context of our clients.

What You’ll Do

Own the roadmap and requirements for the Decision Maker Networks platform.
Lead an empowered team of data scientists and engineers. You bring the problems, customer insight and business context together to find solutions.
Raise the evaluation bar by refining and evolving the standards and assessments built into the platform.
Discover before you build. Spend real time with the people who build on the platform and the clients who rely on its output. Prototype and test tooling with them before committing engineering effort.
Define how we evolve and shape networks, and how the scoring platform leverages these advancements.
Design the tooling and interfaces that give data scientists, Research Operations and client-facing teams the right levers to tune Decision Maker Networks, with the right guardrails. Make the platform extensible enough that data scientists can experiment easily.
Own the business logic and the testing and evaluation harness that Engineering and Data Science use to build networks.
Manage platform launches, define and track the KPIs that measure success, and communicate releases regularly to stakeholders at every level of the company.

Experiences and Capabilities You Bring

5+ years of experience in Product Management, with a significant track record designing and shipping data, ML or algorithmic products.
Outcome Fluency: Ability to trace a modeling decision all the way through to what a Fortune 50 C-suite or PE corporate affairs leader actually experiences, and to prioritize platform work against that impact.
Design-Led Thinking for Expert Users: You refuse to accept that technical tooling is allowed to be confusing. You use design as the primary lens for building a platform whose users are data scientists and analysts working on genuinely hard problems.
Algorithmic Product Intuition: You have partnered with Data Science to ship products where the core of the value is a model, a score or a ranking rather than a screen. You know how to deliver client value with a system whose output is probabilistic, and how to make its behavior legible to the people who depend on it.