Director of Product

Chalice Custom Algorithms

1d•$190,000 - $220,000•Hybrid

About The Position

Chalice is hiring a Director of Product to lead and develop our product management team, reporting to the SVP of Product & Solutions Architecture. You will manage our PMs from day one and partner with the SVP to shape strategy and turn product investments into measurable customer and business results. Our team brings deep media and ad tech expertise and close customer relationships. You will build on those strengths with experience developing PMs, making sound product decisions, and bringing complex data products to market. You will run the day-to-day product management function, with authority over priorities and sequencing within the agreed strategy and investment plan. We are still a startup, and this is a player-coach role. At times, you will directly own an initiative, lead discovery, or write requirements when priorities or team capacity call for it. You will balance that work with coaching and delegate ownership as the team is ready. Dedicated Scrum Master and Technical Project Manager support covers sprint ceremonies and delivery coordination.

Requirements

8+ years of product management experience, including 3+ years directly managing PMs across hiring, coaching, and performance management.
Experience leading a small product team with limited resources and contributing directly to product work when needed.
Strong product judgment, with examples of choosing what to build, defer, or stop and the customer or business results of those decisions.
A track record of developing PMs who grew in judgment, independence, or responsibility.
Experience bringing complex B2B data or ML products into production, working with Engineering and Data Science through uncertainty in data quality, model performance, and technical feasibility.
Clear written and verbal communication; able to frame decisions, write useful requirements, and align technical and commercial stakeholders through changing priorities.
Ability to design meaningful product measures and experiments, interpret results, and weigh customer value against delivery and operating costs.

Nice To Haves

Experience in advertising technology, marketing technology, or an adjacent data-driven marketing domain; programmatic advertising experience is particularly relevant.
Experience with partner integrations, data pipelines, model deployment, or real-time decisioning systems.
Experience turning custom client solutions into reusable platform capabilities or self-service workflows.

Responsibilities

Manage, coach, and develop PMs from day one, holding the team accountable for product outcomes and individual growth. Lead hiring and performance management.
Build on effective practices already in place and improve discovery, prioritization, requirements, and measurement where needed, with structure suited to our size and stage.
Give PMs clear decision authority and development plans. Build shared knowledge and reliable coverage so progress does not depend on one person.
Ensure PMs define the customer problem, intended outcome, scope, and acceptance criteria clearly enough for Engineering and Data Science to assess feasibility and plan the work.
Distinguish research and experiments from work ready for delivery. Agree with technical partners on the evidence needed to proceed, pause, or change direction.
Own product scope and priorities; partner with Engineering and Data Science on technical dependencies, estimates, and readiness, and with the Scrum Master and Technical Project Manager on planning and coordination.
Step in to lead product work where it has the greatest value, from discovery through launch, while maintaining coaching commitments and making deliberate handoffs to PMs.
Partner with the SVP on product strategy and investment priorities. Own portfolio sequencing and resolve tradeoffs that cross product areas or exceed a PM’s authority.
Evaluate new opportunities against customer value, revenue potential, data and infrastructure costs, team capacity, and the work they would displace. Bring clear recommendations to leadership for material investment changes.
Communicate roadmap changes with the rationale, affected commitments, owners, and next decision points. Help teams pause and resume work cleanly as priorities evolve.
Build a discovery practice that includes brands, agencies, and internal users. Use customer and market evidence to test assumptions about what people need and will use.
Partner with Data Science and client-facing teams to define suitable pilot customers, data requirements, success measures, and launch criteria. Distinguish model quality from evidence of customer or business impact.
Work with Sales and Client Solutions on positioning, packaging, and launch readiness. Turn recurring customer needs into repeatable capabilities and make the support required for custom work explicit.
Help customer-facing teams explain what a product can do, where it has limitations, and how results will be measured. Use adoption and performance evidence to guide further investment.