Manager, Analytics

Role Summary & Impact

The Manager, Analytics is a high-visibility, client-facing role responsible for delivering daily performance insights and driving strategic analytics innovation across a portfolio of client accounts.

In this role, you will balance operational excellence—including pacing analysis, campaign performance monitoring, margin analysis, and regular reporting—with strategic innovation projects (~20% of the role), such as supply optimization and outcome-based pricing models. Working alongside backend engineering, data science, and agency client leads, you will take complex programmatic media datasets and build custom, interactive dashboards from scratch while transforming numbers into impactful business narratives.

Key Responsibilities

1. Hands-On Analytics & Dashboard Building

• Build Dashboards from Scratch: Design, construct, and deploy custom interactive dashboards from the ground up using Tableau or Power BI to deliver real-time performance visibility for clients and internal teams.
• Data Manipulation & Querying: Utilize SQL and Python to extract, clean, manipulate, and shape large-scale programmatic and digital media datasets provided by backend engineering teams.
• Operational Reporting & Pacing: Perform regular performance, pacing, and margin analysis across 3–5 assigned client accounts; produce weekly, bi-weekly, and monthly insights reports.

1. Strategic Data Storytelling & Client Consultation

• Translate Data into Actionable Insights: Synthesize complex analytics into clear, compelling executive summaries and narratives that connect media performance to broader client business goals.
• Client & Internal Engagement: Partner closely with internal agency leads and client stakeholders to present analytical findings, answer strategic questions, and guide campaign optimizations.
• Career Growth via Storytelling: Leverage storytelling and presentation opportunities as the primary pathway to grow into leading client engagements and advancing toward an Associate Director role.

1. Innovation, Automation & AI

• Strategic Projects (~20%): Contribute to strategic initiatives, including supply path optimization (SPO), margin analysis, and outcome-based media pricing model development.
• Process Automation: Identify opportunities to automate manual reporting workflows and analytical tools, leveraging AI and scripting to drive operational efficiency and time savings.
• Cross-Functional Collaboration: Serve as the functional bridge between data engineering/infrastructure teams (data pipeline providers) and media activation teams to ensure analytics tools align with operational requirements.

Qualifications & Essential Requirements

• Experience: 3–5 years of experience in marketing analytics, digital media analytics, or agency/ad-tech environments.
• Education: Bachelor’s degree in Business Analytics, Marketing, Economics, Computer Science, Information Systems, or a related field (or equivalent professional experience).
• SQL Proficiency (Required): Strong command of SQL for data querying, aggregation, and performance analysis.
• Python Capabilities (Required): Hands-on experience with Python, specifically applied to data cleaning and manipulation projects (must be able to discuss a practical Python project and its execution).
• Dashboard Building from Scratch (Critical): Demonstrated experience building complete, production-ready dashboards from the ground up in Tableau or Power BI (not just maintaining pre-existing templates).
• Programmatic & Media Understanding: Good understanding of the digital media landscape, ad tech ecosystem, and programmatic advertising fundamentals (e.g., DSPs, ad servers, campaign metrics).
• Data Storytelling & Communication: Exceptional verbal and written communication skills with the proven ability to translate complex data sets into simple, persuasive narratives.
• Critical Thinking & Problem Solving: Strong analytical mindset with the agility to navigate ambiguous business scenarios and propose pragmatic analytical solutions.