Sr. Product Manager

UP.Labs

About The Position

The commercial vehicle and trailer parts aftermarket is large, growing, and structurally fragmented. Dealers make high velocity decisions across siloed systems, inconsistent part taxonomies, substitution chains, OEM constraints, and margin tradeoffs - often in seconds. Despite representing tens of billions of dollars annually in North America, the market remains technologically under digitized. Critical decision logic lives in disconnected data and tribal knowledge. PartsPulse, an UP.Labs company exists to bring structure and clarity to that decision space. Our ambition is to make the invisible structure of parts relationships visible by building the analytical and visual infrastructure required to: Unify fragmented parts and inventory data Create structured substitution and cross reference logic Develop visual mapping systems that make complex part relationships intelligible Embed measurable decision support directly into dealer workflows Quantify downstream impact on wallet share, margin, availability, and throughput The Role This is the first product management hire on the team and a foundational role for the company. You will play a critical part in shaping not just your product domain, but the overall direction of the PartsPulse platform. You will work directly with product leadership and the executive team to define where we place strategic bets, how we measure value, and how we sequence platform evolution. Your thinking will materially influence company direction. We are hiring a Senior Product Manager who combines strategic judgment with deep analytical rigor. This is not a feature factory role. It is a data first, value first position reporting directly into our Vice President of Product and focused on defining measurable customer impact and identifying the highest ROI opportunities to drive durable growth.

Requirements

Strong data driven strategic thinking
Comfort working with AI driven products and translating model capabilities and constraints into clear product requirements
Exceptional analytical rigor and structured problem solving
Process oriented with strong documentation discipline
Ability to operate in ambiguity while imposing clarity and structure
Proven track record leading complex cross functional initiatives in B2B SaaS environments where workflow integration and measurable customer ROI are critical

Nice To Haves

Deep fluency in data systems, analytics, and instrumentation
Comfort working with SQL, data warehouses, or backend systems
Experience building KPI dashboards and customer level reporting frameworks
Exposure to LLM based systems, including prompt iteration or structured evaluation
Familiarity with model evaluation concepts such as datasets, scoring rubrics, success thresholds, reliability measurement, or experimentation loops
Strong intuition for cost versus value tradeoffs in complex, multi stakeholder B2B environments

Responsibilities

Own product vision for a defined area of the platform
Define long term direction, roadmap, and measurable outcomes for your domain
Influence broader platform architecture and sequencing decisions
Contribute meaningfully to company level product strategy
Define and quantify customer value
Establish leading and lagging indicators tied to dealer behavior and business outcomes
Build KPI frameworks connecting product usage to wallet share, margin, inventory turns, and throughput
Anchor initiatives to explicit value hypotheses
Identify and prioritize highest ROI opportunities
Rigorously size opportunities and articulate expected return relative to cost
Recommend sequencing based on leverage, feasibility, and risk
Build the analytical backbone
Partner with engineering on instrumentation and clean data pipelines
Create visibility through dashboards and reporting systems
Drive disciplined execution
Produce structured PRDs that surface tradeoffs and hidden requirements early
Align cross functional stakeholders and drive initiatives from concept through iteration
Mitigate strategic and project level risk through explicit assumptions and validation plans