Senior Manager Analytics

About Dentsu

Led by Dentsu Group Inc. (Tokyo: 4324; ISIN: JP3551520004), a pure holding company established on January 1, 2020, the Dentsu Group encompasses two operational networks: dentsu japan network, which oversees Dentsu's agency operations in Japan, and dentsu international, its international business headquarters in London, which oversees Dentsu's agency operations outside of Japan

With a strong presence in approximately 145 countries and regions across five continents and with 65,000 dedicated professionals, the Dentsu Group provides a comprehensive range of client-centric integrated communications, media and digital services through its five leadership brands—Carat, dentsu X, iProspect, Dentsu Creative, and Merkle—as well as through Dentsu Japan Network companies, including Dentsu Inc., the world's largest single brand agency with a history of innovation.

Role Overview

As a Senior Analytics Manager,you will drive analytics-led decision-making, create high impact insight narratives, manage client facing discussions, and accelerate analytics workflows through automation and generative AI.

You will lead the design and deployment of advanced analytics and ML models across media measurement, marketing effectiveness, and dashboard visualizations.

The role includes a light data engineering component building ETL/ELT pipelines, ensuring data quality, and enabling scalable data foundations for analytics, in partnership with engineering teams.

Key Responsibilities

• Lead experimentation frameworks including A/B testing, brand lift studies, and holdout/geoexperiment design.
• Perform competitive benchmarking using media, audience, pricing, SOV/SOS/SOM, and market share datasets.
• Conduct causal lift analysis, hypothesisbased experimentation, and campaign effectiveness modelling.
• Integrate generative AI and agentic AI (LLMs, AutoML) into modelling workflows for feature generation, automation, and insight summarization.

Insights, Storytelling & Client Leadership

• Deliver compelling analytical narratives, simplifying complex model outputs into actionable insights.
• Lead client conversations across measurement design, modelling outcomes, optimisation strategies, and media planning recommendations.
• Manage stakeholders across media, planning, strategy, product, and engineering teams.

Automation, Tooling & AIEnablement

• Build automation tools using Python scripts, dashboards, and notebooks to streamline analytics workflows.
• Develop selfservice analytics utilities including dashboards and automated reporting modules.
• Create reusable frameworks and accelerators to standardize analytics delivery.

Data Engineering & Data Infrastructure

• Collaborate with data engineering teams to maintain ETL/ELT pipelines using Python, SQL, Airflow/Composer/Prefect.
• Build and optimize analytics-ready datasets and data models powering BI dashboards and measurement frameworks.
• Manage API connectors for ingesting data from Google Ads, Meta Ads, DV360, CM360, LinkedIn, and other marketing platforms.
• Implement data validation, quality checks, and monitoring across pipelines.
• Support cloud-based deployment of ML models using CI/CD, containerization, and orchestration tools.

Required Skills & Experience

Technical Expertise

• 6–10 years of experience in data science, analytics, or marketing science, ideally within media, consulting, or digital marketing analytics environments.
• Strong proficiency in:
• Python (pandas, scikitlearn, ML frameworks for modelling).
• SQL and cloud data warehouses (BigQuery, Snowflake, Synapse, Redshift).
• Google Cloud Platform (GCP) — especially BigQuery, GCS, Cloud Composer.
• Data Visualization & BI Tools, specifically:
• Power BI
• Google Data Studio / Looker Studio
• Creating dashboards for reporting, insight delivery, and campaign measurement.
• Must-have analytical expertise:
• Media Mix Modelling (MMM)
• Multi-touch modelling / attribution principles
• Halo and incrementality analysis
• Regression & forecasting models
• Predictive modelling
• Marketing analytics & media measurement
• Experience with advertising, campaign, impression, and media spend datasets.
• Familiarity with generative AI tools (HuggingFace, LangChain, OpenAI) to accelerate workflows.
• Experience with ML lifecycle monitoring, retraining, and performance tracking.

Good to Have

• Knowledge of broader media measurement approaches: MMM, MTA, competitive benchmarking, ROI modelling, influencer analytics, channel performance analysis.
• Experience with causal inference (uplift modelling, Shapley, double ML).
• Familiarity with feature stores, realtime/batch ML pipelines, MLflow/Seldon.
• Exposure to data quality frameworks like Great Expectations or Monte Carlo.
• Knowledge of containerization (Docker/Kubernetes) and MLOps practices.

Inclusion and Diversity

We're proud to be different and that starts with our people. We believe in equal opportunities for everyone. We won't define people by their race, gender, sexual-orientation, age or disability. Individuality is what makes us great, we want everyone to bring their full self to work and create something amazing. That's what we care about.

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