
Group Head
2 days ago
Client Leadership
• Act as day-to-day analytics lead for our clients, turning briefs into analytical roadmaps
• Present insights to senior brand & media stakeholders; influence decision-making on ~$XX Cr budgets.
• Work closely with media planning and buying teams to embed analytics-driven learning into live campaigns.
• Be the bridge between brand tracking results and tactical media optimizations — ensuring diagnostics turn into action.
Modeling & Methodology
• Lead MMM, Bayesian hierarchical models, incrementality tests, attribution & attention metrics.
• Design KPI frameworks that ladder to brand health, sales, and ROI.
• Drive integration between brand tracking insights and media deployment strategies.
Product & Process
• Shape reusable analytics playbooks (e.g., agile MMM sprints, automated dashboards).
• Partner with product teams to enhance internal tools like Buz AI, Nestup, Auto MMM.
Team Development
• Coach 3-5 analysts: review code (Python/R), set learning paths, enforce best practices.
• Build a culture of experimentation and knowledge-share across accounts.
Thought Leadership
• Publish POVs on marketing science trends; represent the agency in forums & webinars.
• Contribute to new-business pitches with modeling insights.
Must-Have Skills
Statistical & ML chops: regression, Bayesian methods, uplift modeling, causal inference
Marketing analytics toolset: MMM platforms (e.g., Robyn, Meta MMM), GA4/Adobe, SQL/Python/R
Dashboarding: Power BI / Tableau — able to brief data engineers on pipeline requirements
Stakeholder fluency: convert model output into crisp narratives for CMOs & media directors
Team lead exposure: mentored analysts or interns; comfortable assigning tasks & giving feedback
Domain familiarity: alc-bev or CPG advantageous (understanding of ATL/BTL levers, promo cycles)
Nice-to-Have
Experience integrating attention metrics, CEP frameworks, or AI-driven creative diagnostics
Familiarity with Snowflake, dbt, or other modern data-engineering stacks
Certifications in AWS, GCP, or Azure ML services
Success Metrics (First 12 Months)
1. MMM Revamp live in 90 days, delivering ≥ 15 % improvement in model accuracy
2. Quarterly Insight Decks adopted as decision anchor by marketing leadership
3. Analyst NPS ≥ 8/10 on coaching & career growth
4. Process Productivity: 20 % reduction in manual dashboard build time via automation
5. Media Embeddedness: 100% of media plans informed by analytics learnings across key brands
Culture & Mindset
Consultative Curiosity – ask “why” before jumping to “how.”
Bias for Delivery – ship useful models over perfect ones; iterate fast.
Mentor at Heart – treat knowledge transfer as part of the job, not a favor.
Story-first Data – believe insights are only valuable when they travel.
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