Senior Product Manager, Forecasting & Planning Systems
Veho
Product
New York, USA · Remote
USD 145k-160k / year + Equity
About Veho
- Own the roadmap. Set the vision and priorities for Veho's forecasting and planning systems.
- Build the input engine. Replace ad hoc planning workflows with validated, auditable, high-adoption tools used by Customer Success, Revenue Operations, Finance, Transportation, and Ground Operations. Capture off-cycle changes, client ramps, finance assumptions, market signals, and operational feedback in structured form.
- Close the feedback loop. Partner with Data Science to categorize forecast error drivers, accelerate model improvement cycles, and productize forecast accuracy reporting across geography, client, time horizon, and operational segment.
- Drive downstream execution. Push forecast updates and alerts into transportation planning, labor planning, capacity planning, and network orchestration systems. Define escalation workflows so teams can act before forecast error becomes operational failure.
- Run the cadence. Own the cross-functional forecasting working group, including decisions, owners, follow-through, and accountability.
- Ship fast. Use data, SQL, prototypes, and AI tools to move quickly and sharpen product requirements, then partner with Engineering and Data Science to productionize the right solutions.
- Five or more years of product management experience, including ownership of a data-heavy product used by cross-functional business or operations teams.
- Experience with forecasting, planning, capacity management, marketplace balancing, supply chain systems, transportation planning, labor planning, inventory planning, or another operational decision system where input quality and downstream adoption mattered.
- Strong data fluency. You can use SQL or equivalent tools to investigate problems, validate assumptions, and partner credibly with Data Science.
- An eye for human-centered design. You understand that an input tool only works if the people submitting inputs actually use it, and that adoption is the only metric that matters.
- Strong systems thinking. You can trace how a bad input turns into a bad forecast, a bad plan, and an operational miss, then design integrations that prevent that cascade.
- Builder mindset. Personal examples of shipping prototypes solo when needed and partnering with Engineering at the right moment to scale.
- Cross-functional leadership across technical, operations, finance, revenue, and customer-facing stakeholders.
- High ownership. You set up the working group, run the cadence, close the loop with Data Science, and hold stakeholders accountable for their inputs without anyone asking you to.
- Proven track record in last-mile logistics, ecommerce marketplaces, supply chain management, or network and labor planning.
- Prior experience as a product partner to Data Science or Machine Learning teams.
- Deep comfort with ML and statistics, allowing you to operate as a peer to modeling teams rather than just a requestor.
- Versatility in navigating both high-growth startup and mature, scaled environments.