Applied Science Manager

The Role

We're looking for an Applied Science Manager to build and lead Clipboard's Applied Science function, owning the roadmap and vision for science across the marketplace.

You'd be leading a small team of Applied Scientists and growing the function. The team owns the quantitative infrastructure underneath the marketplace: pricing algorithms, auction mechanisms, causal models, metric definitions, and experiment frameworks. Some of that work ships as product; some becomes the analytical substrate every team in the company depends on.

You'll set the bar for the function: defining our key metrics, how we measure them, and how we report on marketplace performance. Teams across product and engineering will build on the models, experiments, and insights your team produces.

This role sits at the intersection of engineering, product, finance, and operations. There will always be more valuable problems than the team can take on, so you'll decide what we work on, in what order, and what success looks like. That means balancing production work with analysis other teams depend on, knowing when a question requires careful causal identification versus a quick directional answer, and pushing back when the expected value isn't there. Priorities will shift, and you'll keep the team focused on the highest-impact work.

You'll also hire and develop the Applied Science team. This is a player-coach role: you'll mentor Applied Scientists across levels while staying close enough to the work to take on important IC problems yourself.

Our toolkit includes causal inference, machine learning, randomized experiments, discrete-time hazard models, auction/mechanism design, and time series analysis. You'll work directly with engineers to take models from prototype to production and communicate your reasoning clearly to PMs, operators, and leadership.

Minimum Requirements

• Bachelor’s degree in economics, statistics, engineering, mathematics, or another quantitative field, or equivalent practical experience.

• Experience building and deploying quantitative models in applied or research settings.

• Fluency querying data directly with SQL or an equivalent tool.

• Experience designing and analyzing controlled experiments.

• 1-3 years of experience managing or leading a team.

Who Thrives Here

• PhD/Masters in economics, operations research, statistics, engineering, or a related field, or equivalent quantitative depth from research or trading.

• Track record of taking prediction models from idea to production.

• Strong grounding in experimental design and causal inference.

• Experience in quantitative finance, economic consulting, marketplaces, or another data-intensive environment where decisions have real business consequences.