Negotiable
Undetermined
Hybrid
Remote or Blue Ash, Ohio
Summary: The Product Manager Level 2 role at Kforce involves managing the technical aspects of a product throughout its lifecycle, collaborating with various stakeholders to ensure deliverables are met. The position requires the creation and maintenance of product catalogs and technology roadmaps, as well as the analysis of product metrics to enhance customer experience. The role also includes defining requirements, managing expectations, and leading teams to refine and prioritize product features. Strong knowledge of data concepts and machine learning fundamentals is essential for success in this position.
Key Responsibilities:
- Manage all technical aspects of product through product lifecycle
- Work directly and indirectly with business stakeholders, vendors and third parties to ensure execution of deliverables
- Create, maintain, and communicate product catalog and technology roadmaps, including near-term delivery, to engage stakeholders across the organization
- Identify, measure, and improve key product catalog metrics to enhance the customer experience, and create a compelling, relevant product vision using web metrics, customer insights, feedback, research and internal operational metrics
- Elicit, define, and analyze medium to complex requirements in various formats ensuring they are testable, measurable and traceable
- Set criteria for minimum viable product to increase the speed/frequency with which enhancements and new capabilities are delivered
- Lead the appropriate teams to refine, prioritize and manage requirements using various tools (e.g., templates, team backlogs, requirements management or agile task management applications)
- Lead requirement walk-throughs with key stakeholders using various methods (e.g., team demos, workshops, sprint planning and backlog refinement sessions)
- Identify and estimate anticipated work efforts based on priority using requirement work plans, program increment (PI) planning, and sprint planning
- Define and resolve dependencies, issues and risks and identify impacted areas through team collaboration
- Break down a medium to complex vision into smaller projects, initiatives, or features
- Stakeholder Management
- Align business leaders, engineers, data scientists, legal/compliance, and ops
- Translate technical constraints into business-relevant language
- Manage expectations around ML uncertainty and iteration
Key Skills:
- Product strategy and prioritization
- Data platform fundamentals
- ML literacy
- Stakeholder communication
- Designing for expert users without alienating new ones
- Clear documentation and onboarding flows
- Understanding user workflows-not just APIs
- MLOps understanding
- Experimentation and metrics fluency
- Responsible AI leadership
- Platform UX thinking
- Data types: structured, semi-structured, unstructured
- Data pipelines (batch vs. streaming)
- Data quality dimensions: accuracy, completeness, timeliness
- Data lineage and observability
- Metadata, schemas, and versioning
- APIs, SDKs, and self-service capabilities
- Multi-tenant vs. single-tenant design
- Performance, scalability, and cost tradeoffs
- Internal vs. external (customer-facing) platforms
- Supervised vs. unsupervised learning
- Training vs. inference
- Features, labels, and training data
- Model evaluation metrics (precision, recall, AUC, RMSE, etc.)
- Overfitting vs. generalization
- Model training pipelines
- Model deployment patterns (batch, real-time, edge)
- Model monitoring and retraining
- Versioning of models and data
- Rollbacks and experimentation (A/B tests, canary releases)
Salary (Rate): £60 hourly
City: Blue Ash
Country: United States
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
RESPONSIBILITIES:
Kforce has a client that is seeking a Product Manager Level 2 in Blue Ash, OH.
Key Responsibilities:
* Manage all technical aspects of product through product lifecycle
* Work directly and indirectly with business stakeholders, vendors and third parties to ensure execution of deliverables
* Create, maintain, and communicate product catalog and technology roadmaps, including near-term delivery, to engage stakeholders across the organization
* Identify, measure, and improve key product catalog metrics to enhance the customer experience, and create a compelling, relevant product vision using web metrics, customer insights, feedback, research and internal operational metrics
* Elicit, define, and analyze medium to complex requirements in various formats ensuring they are testable, measurable and traceable
* Set criteria for minimum viable product to increase the speed/frequency with which enhancements and new capabilities are delivered
* Lead the appropriate teams to refine, prioritize and manage requirements using various tools (e.g., templates, team backlogs, requirements management or agile task management applications)
* Lead requirement walk-throughs with key stakeholders using various methods (e.g., team demos, workshops, sprint planning and backlog refinement sessions)
* Identify and estimate anticipated work efforts based on priority using requirement work plans, program increment (PI) planning, and sprint planning
* Define and resolve dependencies, issues and risks and identify impacted areas through team collaboration
* Break down a medium to complex vision into smaller projects, initiatives, or features
* Stakeholder Management
* Align business leaders, engineers, data scientists, legal/compliance, and ops
* Translate technical constraints into business-relevant language
* Manage expectations around ML uncertainty and iteration
REQUIREMENTS:
* Product strategy and prioritization
* Data platform fundamentals
* ML literacy
* Stakeholder communication
* Designing for expert users without alienating new ones
* Clear documentation and onboarding flows
* Understanding user workflows-not just APIs
Strong Differentiators:
* MLOps understanding
* Experimentation and metrics fluency
* Responsible AI leadership
* Platform UX thinking
Data Concepts You Should Be Fluent In:
* Data types: structured, semi-structured, unstructured
* Data pipelines (batch vs. streaming)
* Data quality dimensions: accuracy, completeness, timeliness
* Data lineage and observability
* Metadata, schemas, and versioning
Platform Thinking:
* APIs, SDKs, and self-service capabilities
* Multi-tenant vs. single-tenant design
* Performance, scalability, and cost tradeoffs
* Internal vs. external (customer-facing) platforms
Machine Learning Fundamentals Every PM Should Know:
* Supervised vs. unsupervised learning
* Training vs. inference
* Features, labels, and training data
* Model evaluation metrics (precision, recall, AUC, RMSE, etc.)
* Overfitting vs. generalization
* ML Product Realities
* ML outputs are probabilistic, not deterministic
* Model performance degrades over time (data drift, concept drift)
* Improving models often requires better data, not better algorithms
* ML development is experimental and iterative
Areas that must be understood:
* Model training pipelines
* Model deployment patterns (batch, real-time, edge)
* Model monitoring and retraining
* Versioning of models and data
* Rollbacks and experimentation (A/B tests, canary releases)
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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