onsite

Director - Data Science - Dentsu

Data Scientist

Job Description: Required Qualifications Location: Brand: Time Type: Contract Type:

About the role

Lead the DGS Data Science team, managing workload allocation, quality standards, and delivery timelines
Own end-to-end model development for MMM, incrementality, RBA, and forecasting across client portfolios
Manage 3rd Party Agentic Analytics client pilot setup: data preparation, model configuration, validation, and handoff to Media Effectiveness teams
Develop GTM strategy POV and recommendations briefs for 3rd Party Agentic Analytics product expansion
Establish methodology standards and model validation frameworks that ensure consistency across all client engagements
Partner with the VP, Data Science on strategic decisions around model architecture, tooling, and team capability building
Work with the AI Agents team to make models agentic: define APIs, output schemas, and interfaces that agents can consume
Train and mentor Data Scientists and Senior Data Scientists on Bayesian methods, causal inference, and client communication
Create reusable model templates, documentation, and training materials that accelerate future client deployments
Coordinate with Data Architecture on data requirements, pipeline dependencies, and quality standards

Job Description:

Required Qualifications

7+ years of experience in data science or quantitative analytics with 2+ years in a leadership/mentorship role
Expert-level knowledge of marketing mix modeling, econometrics, and causal inference methods
Deep proficiency in Bayesian modeling (PyMC, Meridian) and frequentist statistical methods
Strong Python and SQL skills with emphasis on reproducible, well-documented analytical code
Experience managing model development lifecycles from research through production deployment
Track record of building and leading data science teams in a delivery-focused environment
Excellent communication skills for translating complex methodology into business recommendations
Experience with project management and workload planning across multiple concurrent engagements

Location:

Brand:

Time Type:

Contract Type:

About the role

Lead the DGS Data Science team, managing workload allocation, quality standards, and delivery timelines
Own end-to-end model development for MMM, incrementality, RBA, and forecasting across client portfolios
Manage 3rd Party Agentic Analytics client pilot setup: data preparation, model configuration, validation, and handoff to Media Effectiveness teams
Develop GTM strategy POV and recommendations briefs for 3rd Party Agentic Analytics product expansion
Establish methodology standards and model validation frameworks that ensure consistency across all client engagements
Partner with the VP, Data Science on strategic decisions around model architecture, tooling, and team capability building
Work with the AI Agents team to make models agentic: define APIs, output schemas, and interfaces that agents can consume
Train and mentor Data Scientists and Senior Data Scientists on Bayesian methods, causal inference, and client communication
Create reusable model templates, documentation, and training materials that accelerate future client deployments
Coordinate with Data Architecture on data requirements, pipeline dependencies, and quality standards

Job Description:

Required Qualifications

7+ years of experience in data science or quantitative analytics with 2+ years in a leadership/mentorship role
Expert-level knowledge of marketing mix modeling, econometrics, and causal inference methods
Deep proficiency in Bayesian modeling (PyMC, Meridian) and frequentist statistical methods
Strong Python and SQL skills with emphasis on reproducible, well-documented analytical code
Experience managing model development lifecycles from research through production deployment
Track record of building and leading data science teams in a delivery-focused environment
Excellent communication skills for translating complex methodology into business recommendations
Experience with project management and workload planning across multiple concurrent engagements

Location:

Brand:

Time Type:

Contract Type: