Senior Analytics Manager
Location: Singapore
Time Type: Full time
Job Description
Job Description:
About the job
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
Advanced Analytics, Media Measurement & Modelling
Develop and operationalize machine learning models including Media Mix Modelling (MMM), multi‑touch modelling, halo/incrementality analysis, regressions, predictive models, and time‑series forecasting.
Lead experimentation frameworks including A/B testing, brand lift studies, and holdout/geo‑experiment design.
Perform competitive benchmarking using media, audience, pricing, SOV/SOS/SOM, and market share datasets.
Conduct causal lift analysis, hypothesis‑based experimentation, and campaign effectiveness modelling.
Integrate generative AI and agentic AI (LLMs, AutoML) into modelling workflows for feature generation, automation, and insight summarization.
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.
Build automation tools using Python scripts, dashboards, and notebooks to streamline analytics workflows.
Develop self‑service analytics utilities including dashboards and automated reporting modules.
Create reusable frameworks and accelerators to standardize analytics delivery.
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, scikit‑learn, 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.
Soft Skills
Strong communication and storytelling ability — able to translate analytical outputs into business language.
Strong stakeholder and client management skills.
High analytical curiosity, attention to detail, and problem-solving strength.
Collaborative mindset across analytics, engineering, product, and strategy teams.
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.
Dentsu Values
Will live the dentsu 8 Ways at all times: We Dream Loud, We Inspire Change, We Team Without Limits, We All Lead, We Make It Real, We Climb High, We Choose Excitement, We Are A Force For Good.
#LI-DNI
Location:
SingaporeBrand:
IprospectTime Type:
Full timeContract Type:
PermanentThere are more than 50,000 engineering jobs:
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