Key Responsibilities
Product & Portfolio Planning: Define product scope, roadmaps, priorities, requirements, and implementation plans for a portfolio of data, AI, and digital solutions, ensuring alignment with company goals and Objectives & Key Results (OKRs).
Product Development & Execution: Lead end-to-end product development across Product Planning, R&D, Business Engineering, IT, Data, and AI teams; drive requirements definition, backlog prioritization, development, testing, deployment, and continuous improvement.
Data Analysis & Insights: Analyze business, product, and operational data to identify trends, patterns, process gaps, and improvement opportunities; translate data insights into actionable product requirements and business recommendations.
AI-Enabled Product Solutions: Identify and prioritize AI, GenAI, analytics, automation, and digital opportunities that improve planning, decision-making, and operational productivity; develop product requirements and drive solutions from proof-of-concept to scaled adoption.
Data & Technical Requirements: Define data requirements, business rules, system interfaces, APIs, integration requirements, and acceptance criteria; collaborate with engineering, Data, AI, and IT teams to ensure technical solutions meet business and product needs.
Product Metrics & Analytics: Define and track product KPIs and performance indicators, including usage, adoption, accuracy, productivity, cycle time, and business outcomes; leverage data-driven insights to prioritize product enhancements and continuous improvement.
Quality Assurance & Data Validation: Establish data quality requirements, validation rules, acceptance criteria, and review gates for data, AI, and digital solutions; ensure solutions are accurate, reliable, scalable, and meet stakeholder expectations before deployment.
Stakeholder Engagement & Communication: Build alignment with business, technical, and leadership stakeholders; translate business needs into actionable product and technical requirements; and communicate product strategy, data insights, progress, risks, and outcomes to executive audiences.
Product Adoption & Continuous Improvement: Drive product adoption through stakeholder engagement, user feedback, usage analytics, training, and continuous improvement to ensure data, AI, and digital capabilities deliver sustainable business value.
Qualifications
Qualifications
Bachelor’s degree in Data Science, Data Analytics, Engineering, Information Technology, Information Systems, Computer Science, or a related technical discipline.
Minimum of 8–10 years of relevant experience in technical product management, data analytics, business intelligence, software/data solutions, digital transformation, or related technology roles, preferably within a technology organization.
Strong experience in data analysis and data-driven decision-making, with the ability to explore complex datasets, identify trends and patterns, develop insights, and translate findings into product requirements and business actions.
Experience defining product requirements, user stories, business rules, data requirements, acceptance criteria, and product roadmaps, with familiarity with Agile product development and the software development lifecycle.
Working knowledge of data technologies and software/data architecture concepts, including data modeling, databases, data pipelines, system integration, and enterprise applications. Experience with Python, cloud data platforms, or comparable technologies is an advantage.
Experience or strong exposure to AI, machine learning, GenAI, analytics, automation, or digital solutions, with the ability to evaluate business use cases and work effectively with technical teams to bring solutions into production.
Strong stakeholder management and communication skills, with the ability to work across business, engineering, data, AI, and leadership teams and communicate technical or analytical concepts clearly to technical and non-technical audiences.
Ability to balance business value, user needs, data insights, technical feasibility, and attention to detail, while operating effectively in a fast-paced and evolving technology environment.
PMP, Agile, Lean, or Six Sigma certification is an added advantage.
Why This Role Matters
This role sits at the intersection of product management, data, technology, and digital transformation, turning business needs and insights into scalable product solutions and measurable business outcomes.
By driving data-driven product decisions, cross-functional collaboration, and effective execution, this role delivers solutions that enhance user experience, improve productivity, and create sustainable value across the organization.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
Role Overview
The Product Manager is accountable for defining and driving data-driven products, AI solutions, analytics, and digital capabilities that improve planning, decision-making, productivity, and operational efficiency across the organization.
The role combines product management, data analysis, business understanding, and technical knowledge to translate business needs and data insights into product requirements and scalable technology solutions.
The successful candidate will work cross-functionally with Product Planning, R&D, Business Engineering, Data/AI teams, IT, and leadership to identify opportunities, define requirements, prioritize product capabilities, and deliver solutions from concept through deployment and adoption.
Key Responsibilities
Product & Portfolio Planning: Define product scope, roadmaps, priorities, requirements, and implementation plans for a portfolio of data, AI, and digital solutions, ensuring alignment with company goals and Objectives & Key Results (OKRs).
Product Development & Execution: Lead end-to-end product development across Product Planning, R&D, Business Engineering, IT, Data, and AI teams; drive requirements definition, backlog prioritization, development, testing, deployment, and continuous improvement.
Data Analysis & Insights: Analyze business, product, and operational data to identify trends, patterns, process gaps, and improvement opportunities; translate data insights into actionable product requirements and business recommendations.
AI-Enabled Product Solutions: Identify and prioritize AI, GenAI, analytics, automation, and digital opportunities that improve planning, decision-making, and operational productivity; develop product requirements and drive solutions from proof-of-concept to scaled adoption.
Data & Technical Requirements: Define data requirements, business rules, system interfaces, APIs, integration requirements, and acceptance criteria; collaborate with engineering, Data, AI, and IT teams to ensure technical solutions meet business and product needs.
Product Metrics & Analytics: Define and track product KPIs and performance indicators, including usage, adoption, accuracy, productivity, cycle time, and business outcomes; leverage data-driven insights to prioritize product enhancements and continuous improvement.
Quality Assurance & Data Validation: Establish data quality requirements, validation rules, acceptance criteria, and review gates for data, AI, and digital solutions; ensure solutions are accurate, reliable, scalable, and meet stakeholder expectations before deployment.
Stakeholder Engagement & Communication: Build alignment with business, technical, and leadership stakeholders; translate business needs into actionable product and technical requirements; and communicate product strategy, data insights, progress, risks, and outcomes to executive audiences.
Product Adoption & Continuous Improvement: Drive product adoption through stakeholder engagement, user feedback, usage analytics, training, and continuous improvement to ensure data, AI, and digital capabilities deliver sustainable business value.
Qualifications
Bachelor’s degree in Data Science, Data Analytics, Engineering, Information Technology, Information Systems, Computer Science, or a related technical discipline.
Minimum of 8–10 years of relevant experience in technical product management, data analytics, business intelligence, software/data solutions, digital transformation, or related technology roles, preferably within a technology organization.
Strong experience in data analysis and data-driven decision-making, with the ability to explore complex datasets, identify trends and patterns, develop insights, and translate findings into product requirements and business actions.
Experience defining product requirements, user stories, business rules, data requirements, acceptance criteria, and product roadmaps, with familiarity with Agile product development and the software development lifecycle.
Working knowledge of data technologies and software/data architecture concepts, including data modeling, databases, data pipelines, system integration, and enterprise applications. Experience with Python, cloud data platforms, or comparable technologies is an advantage.
Experience or strong exposure to AI, machine learning, GenAI, analytics, automation, or digital solutions, with the ability to evaluate business use cases and work effectively with technical teams to bring solutions into production.
Strong stakeholder management and communication skills, with the ability to work across business, engineering, data, AI, and leadership teams and communicate technical or analytical concepts clearly to technical and non-technical audiences.
Ability to balance business value, user needs, data insights, technical feasibility, and attention to detail, while operating effectively in a fast-paced and evolving technology environment.
PMP, Agile, Lean, or Six Sigma certification is an added advantage.
Why This Role Matters
This role sits at the intersection of product management, data, technology, and digital transformation, turning business needs and insights into scalable product solutions and measurable business outcomes.
By driving data-driven product decisions, cross-functional collaboration, and effective execution, this role delivers solutions that enhance user experience, improve productivity, and create sustainable value across the organization.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
