Role
- Manager – Digital Analytics, Insights & Optimization

Experience:
10-18 Years Shift: 3 PM Onwards Position: Remote Tech Stack: Mentioned in IAS Sheet (GA4, Adobe Analytics, Power BI, Big Query, CRO, Claude AI)

Job Description
(Manager – Digital Analytics, Insights & Optimization) Role Purpose Lead digital analytics, AI-powered insights, experimentation, and personalization programs by managing a high-performing team that transforms customer data into measurable business outcomes. Role Overview We are seeking an experienced leader to manage a specialised team focused on digital analytics, business intelligence, experimentation, and website optimization. The role is responsible for defining strategy and driving the execution and delivery of analytics reporting, actionable insights, conversion rate optimization (CRO), personalization initiatives, and AI-powered analytics solutions that deliver measurable business impact. The individual will serve as the primary liaison between business stakeholders, marketing teams, digital product owners, and technical resources, ensuring that data-driven initiatives are prioritised, delivered on time, and aligned with organisational objectives.

Key Responsibilities
# Delivery Leadership
• Own the end-to-end delivery of analytics, reporting, optimization, and personalization initiatives.
• Develop and manage roadmaps, sprint plans, delivery milestones, and stakeholder commitments.
• Ensure timely execution of analytics implementations, dashboard development, experimentation programs, and optimization initiatives.
• Monitor delivery KPIs and proactively manage risks, dependencies, and bottlenecks.
• Establish delivery governance, quality standards, and operational processes. # Analytics & Insights Management
• Oversee the development and maintenance of reporting solutions using: ◦ Google Analytics 4 (GA4) ◦ Adobe Analytics ◦ Power BI ◦ Big Query ◦ AI-powered analytics platforms, including Claude and LLM-based insight solutions
• Ensure reporting frameworks deliver actionable business insights rather than data-only outputs.
• Drive the adoption of self-service reporting and executive dashboards.
• Partner with stakeholders to define measurement strategies, business KPIs, and performance frameworks.
• Translate analytics findings into actionable recommendations that support business decisions. # Data & Technology Leadership




• Guide the effective integration and utilisation of the following technologies: ◦ Google Analytics 4 (GA4) ◦ Adobe Analytics ◦ BigQuery ◦ Power BI ◦ Claude AI, Claude Code, and GenAI-assisted analytics tools ◦ Optimizely ◦ Contentsquare
• Establish best practices for tracking, tagging, data quality, and analytics governance.
• Support AI-driven analytics, automated reporting, and insight-generation initiatives.
• Promote scalable, reliable, and maintainable analytics solutions. # Experimentation & Optimization Leadership
• Define and lead the experimentation, conversion optimization, and personalization roadmap.
• Oversee A/B testing, multivariate testing, and website personalization initiatives.
• Ensure accurate measurement and evaluation of experimentation outcomes and business impact.
• Drive a culture of data-driven decision-making through structured experimentation.
• Identify opportunities to improve customer journeys, engagement, and conversion rates. # Stakeholder & Client Management
• Act as the primary point of contact for business, marketing, digital product, and leadership stakeholders.
• Serve as a trusted advisor to clients and business leaders on analytics and optimization strategies.
• Translate business objectives into measurable analytics, experimentation, and optimization programs.
• Present insights, performance trends, solution recommendations, and business outcomes to senior stakeholders.
• Manage stakeholder expectations, delivery priorities, and cross-functional alignment. # Team Leadership & Development
• Provide technical and people leadership to specialist resources across three functional areas (Analytics Reporting Lead, Analytics Engineering Lead & Optimization & Personalization Lead) Required Skills & Experience # Skilled Experience
• 10+ years of experience in digital analytics, optimization, consulting, or delivery management.
• 5+ years of experience leading analytics, experimentation, or digital marketing technology teams.
• Proven experience managing stakeholder-facing analytics and optimization programs.




• Demonstrated ability to lead cross-functional teams and deliver business-critical initiatives. # Technical Expertise Strong working knowledge of:
• Google Analytics 4 (GA4)
• Adobe Analytics
• Power BI and executive dash boarding
• BigQuery and analytics data management
• Optimizely and experimentation platforms
• Contentsquare and digital experience analytics
• Conversion rate optimization (CRO)
• Website personalization
• Digital measurement frameworks and KPI development
• Generative AI and LLM-powered analytics applications
• Analytics automation and AI-assisted reporting workflows # Leadership & Management Skills
• Delivery governance and quality management
• Program and project management
• People leadership and team development
• Stakeholder and client relationship management
• Executive communication and presentation
• Risk and dependency management
• Prioritization, planning, and resource allocation
• Strategic thinking and business problem-solving # Preferred Qualifications
• Bachelor's degree in Computer Science, Information Technology, or a related discipline.
• Master's degree or a specialised qualification in Analytics is an advantage.
• Experience managing digital transformation or customer experience analytics programs.
• Relevant certifications in Google Analytics, Adobe Analytics, Power BI, Agile/Scrum, or Optimizely.
• Experience leveraging AI and automation to improve analytics and reporting workflows.
• Experience delivering consulting services or managing client-facing engagements. What Success Looks Like:
• Business problems are addressed through integrated, scalable solutions rather than isolated implementations.
• Analytics, data engineering, experimentation, and personalization operate as a connected ecosystem.
• Teams have clear technical direction, architectural standards, and delivery governance.
• AI capabilities are effectively leveraged to accelerate insights, reporting, and automation.
• Stakeholders recognise the role as a trusted advisor for analytics and optimization initiatives.
• Analytics, optimization, and reporting capabilities are enhanced through AI-powered automation and Claude MCP integrations, resulting in faster delivery, reduced operational effort, and increased business impact. Thanks & Regards Vaishali Bhola [email protected] (phone hidden)

📌 Manager – Digital Analytics, Insights (Noida)
🏢 Trantor
📍 Noida