Business Lead, Digital Product Management

Job Summary

The Digital Product Management Business Lead is an experienced role bridging business needs and digital solutions while leading and developing a team of professionals.

The Digital Product Management Business Lead translates business needs into clear, actionable requirements that enable successful delivery and adoption of digital, analytics, automation, data science, and AI products. The role works across business, product, design, data, engineering, quality, and technology partners to identify business needs, define requirements and future-state capabilities, shape product priorities, and guide digital solutions from discovery through implementation and continuous improvement.

This role collaborates closely with Product Managers, and is responsible for leading and developing a team, setting priorities, managing performance, and strengthening business analysis and product management capabilities

Location: Bangalore, Karnataka, India

Responsibilities

Business Analysis & Problem Definition

• Partner with business stakeholders, product teams and business analysts to ensure strategic priorities, business processes, pain points, opportunities, risks, and desired outcomes are effectively understood and documented.
• Guide and mentor business analysts in planning and facilitating discovery sessions through stakeholder interviews, workshops, process analysis, data analysis and user research.
• Provide oversight and direction on process and systems assessments, business requirements documentation, epics, user stories, process flows, and acceptance criteria ensuring solutions align with business objectives and product management best practices.
• Review and coach analysts on developing structured recommendations and business cases that support informed decision-making and investment prioritization.

Digital Product Management

• Lead and develop business analysts, providing guidance on product management practices, prioritization, and execution.
• Support adherence to product management frameworks, governance processes, and ways of working to ensure consistency across products and teams.
• Oversee product vision, roadmaps, backlogs and establish clear priorities for delivery teams.
• Partner with engineering, architecture, data, UX/design, and other teams throughout the product development lifecycle.
• Identify opportunities to leverage digital technologies, data, automation, analytics, and AI to improve business outcomes, assessing whether AI is the appropriate solution based on value, user need, data readiness, feasibility, risk, and required oversight.

Product Performance & Business Value

• Review and coach analysts on defining measurable product outcomes, KPIs, adoption metrics, and value measures, including relevant measures for AI-enabled capabilities such as reliability, output quality, user trust, exception rates, and productivity improvement.
• Monitor product performance and identify opportunities for optimization and enhancement, using AI-assisted analysis to detect patterns, adoption barriers, emerging risks, and improvement opportunities.
• Track expected and realized value from digital investments, using AI to synthesize performance, financials, adoption, and user data.
• Recommend whether products or capabilities should be enhanced, scaled, consolidated, or retired based on value, performance, adoption, risks, and strategic fit.

Stakeholder & Cross-functional Leadership

• Serve as a key connection point between SCE Product Managers and Business Analyst using AI-assisted synthesis to improve shared understanding of needs, decisions, requirements, and delivery implications.
• Build alignment across stakeholders with differing priorities and perspectives, using AI to organize inputs, compare options, clarify areas of agreement, conflict, and unresolved risks.
• Facilitate decisions on requirements, priorities, scope, trade-offs, and delivery, using AI-supported analysis to present options and implications while ensuring accountable stakeholders make final decisions.
• Communicate product roadmaps, progress, risks, dependencies, and outcomes to leadership, using approved AI tools to accelerate concise, audience-appropriate updates that are reviewed for accuracy and context.
• Translate technical and AI concepts, capabilities, limitations, risks, and trade-offs into clear business language, and translate business needs into actionable direction for technology teams.

People Management & Team Development

• Manage, coach, and develop a team of business analysts, product professionals, and related roles, including building their ability to use approved AI tools responsibly to improve work quality, speed, and business impact.
• Establish clear objectives, priorities, roles, and performance expectations, including expectations for appropriate AI use, verification of outputs, data protection, and accountability for final work products.
• Provide ongoing feedback, coaching, performance management, and career development, using AI-assisted preparation where appropriate while retaining personal judgment and accountability for employee decisions.
• Allocate work and resources based on priorities, capacity, skills, and development opportunities, using AI-supported workload and scenario analysis to inform-not determine-management decisions.
• Mentor team members in business analysis, product management, stakeholder engagement, Agile ways of working, and responsible application of AI to research, synthesis, requirements, testing, and communication.
• Establish consistent standards and best practices for requirements, product documentation, prioritization, delivery, and AI-assisted ways of working, including validation, traceability, privacy, security, and governance expectations.
• Identify capability gaps and create development plans to strengthen team effectiveness, including AI literacy, prompt and context design, critical evaluation of outputs, data fluency, and value measurement.
• Foster a collaborative, accountable, and high-performing team culture that encourages responsible experimentation, shared learning, and scaling of proven AI-enabled practices.

Other Duties

• Cultivate and sustain collaboration across teams to build trust, open communication, and shared ownership of project goals.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.