Product Manager

Location
:
Blue Ash, OH (Onsite 5 days/week)

Employment Type
:
Contract (W2, 1099, or C2C)

Duration
: 6+ months (possible extension and potential conversion to direct employee with end client)

Compensation
: $65–$70/hour | Equivalent to ~$135,00 – $146,000/year

Travel
:
None

Start
: ASAP

Open Role Due To
:
Platform build and expansion

Our client, a leading national retailer, is seeking a Product Manager to support an eCommerce fulfillment environment spanning pickup, third-party delivery (Instacart, Door Dash), and store operations. The team is building a platform focused on order submission, item selection, and routing, with emphasis on operational reporting, process optimization, and demand forecasting.

This role owns product planning and execution across the full product lifecycle—gathering and prioritizing requirements, defining vision and success metrics, and delivering platform capabilities that drive revenue, operational efficiency, and customer satisfaction. You’ll balance technical feasibility, ML realities, and business outcomes while aligning stakeholders across engineering, data science, operations, vendors, and business leaders.

Record your short intro here & tell us about your platform product experience, your ML/data fluency, and why building workflow-first tools for high-volume eCommerce fulfillment excites you.

• Own and manage the technical aspects of the product lifecycle from concept through delivery and ongoing optimization
• Develop, maintain, and communicate product strategy and technology roadmaps (including near‑term delivery plans) to align stakeholders
• Partner with business stakeholders, vendors, and third parties to ensure successful execution of product deliverables
• Define product vision and success metrics using customer insights, analytics, feedback, research, and operational data
• Identify, track, and improve key product performance metrics to enhance customer experience and business outcomes
• Elicit, analyze, and document medium‑to‑complex requirements in testable, measurable, and traceable formats
• Define MVP criteria to accelerate delivery of enhancements and net‑new capabilities
• Lead backlog refinement, prioritization, and requirement management using Agile tools and structured methodologies
• Facilitate requirement walkthroughs, workshops, sprint planning, and PI planning sessions to ensure alignment
• Break down complex platform vision into actionable initiatives, features, and user stories
• Identify and manage dependencies, risks, and issues; drive cross‑team collaboration to resolve blockers
• Estimate work effort and support release planning to ensure predictable, high‑quality delivery
• Design for expert users without alienating new users through workflow‑first experiences, clear documentation, and onboarding flows (not just API‑first thinking)

• High‑impact platform work tied directly to fulfillment speed, cost, and customer promise
• Exposure to ML‑driven demand forecasting and operational intelligence in a high‑volume environment
• Ownership of critical workflow surfaces (submission, selection, routing) used by expert operators and technical teams
• Opportunity to shape operational reporting and process optimization at scale

• Experience defining product strategy and driving prioritization decisions
• Strong understanding of data platform fundamentals and modern data architectures
• ML literacy (training vs. inference, supervised vs. unsupervised learning, evaluation metrics)
• Fluency in core data concepts: structured/semi‑structured/unstructured data; batch vs. streaming pipelines; data quality (accuracy, completeness, timeliness); data lineage and observability; metadata, schemas, and versioning
• Strong stakeholder communication skills across technical and non‑technical audiences
• Experience designing products for expert or highly technical users

• MLOps knowledge and experience working with model lifecycle processes (monitoring, retraining, rollback strategies, controlled experimentation)
• Experimentation and metrics expertise (A/B testing, success measurement frameworks)
• Responsible AI leadership or governance experience
• Platform‑focused UX mindset with experience building scalable, self‑serve capabilities (APIs, SDKs, internal portals)