At a glanceSummarised by Seekless from the posting.
Must have10
Strong proficiency in Python for data analysis and machine learning
Solid SQL skills, comfortable working with large, complex datasets
Working knowledge of GCP, particularly BigQuery; familiarity with cloud-based data pipelines
Practical experience building lead scoring and churn prediction models
Experience with or strong conceptual understanding of Media Mix Modeling (e.g., adstock, saturation curves, Bayesian approaches such as Meridian, Robyn, or PyMC-Marketing is a plus)
Good understanding of media and marketing concepts — campaigns, channels, funnels, attribution, and marketing KPIs
Ability to communicate technical findings to non-technical stakeholders, including clients
Willingness to build expertise in Google Ads Data Hub (ADH), or prior exposure to ADH study types
Bachelor's/Master's degree in Statistics, Computer Science, Data Science, Economics, or a related quantitative field
2–5 years of relevant experience in data science/analytics roles
Nice to have4
Experience with GA4, Google Ads, Meta Ads, or other marketing platform data
Exposure to reverse ETL / audience activation workflows
Experience with Looker Studio, Power BI, or similar BI tools
Prior experience in a media agency, ad-tech, or martech environment
Eligibility1
We are an equal opportunity employer and welcome applicants irrespective of age, sex, race, ethnicity, disability and other factors that have no bearing on an individual’s ability to perform their job
Skills
Python
pandas
scikit-learn
statsmodels
SQL
Google Cloud Platform (GCP)
BigQuery
Cloud Run
Cloud Functions
IAM
Media Mix Modeling (MMM)
Meridian
Robyn
PyMC-Marketing
Google Ads Data Hub (ADH)
GA4
Google Ads
Meta Ads
Looker Studio
Power BI
Agency :
PivotRoots
Job Description :
Havas CSA is looking for a Data Scientist to join our analytics team, working on marketing and media analytics problems across FMCG, BFSI, retail, and automotive clients. The role blends hands-on statistical/ML modeling with a strong understanding of media and marketing performance and requires the ability to translate business questions into data solutions that clients can act on.
Key Responsibilities:
•
Build and maintain lead scoring models to prioritize high-intent customers/prospects for sales and marketing teams
•
Develop churn prediction models to identify at-risk customers and support retention strategies
•
Design and execute Media Mix Modeling (MMM) studies to measure channel-level marketing effectiveness and guide budget allocation
•
Write efficient SQL queries to extract, transform, and validate data from large marketing and transactional datasets
•
Build and productionize data pipelines and models in Python (pandas, scikit-learn, statsmodels, or equivalent)
•
Work within Google Cloud Platform (GCP) — BigQuery, Cloud Run/Functions, IAM, and related services — to build scalable data workflows
•
Translate model outputs into clear, business-relevant recommendations for marketing and media teams
•
Collaborate with client servicing, media planning, and analytics teams to embed data science outputs into campaign and business decisions
•
Stay current on marketing measurement approaches (attribution, incrementality, media effectiveness) and apply them to client problems
Required Skills & Experience:
•
Strong proficiency in Python for data analysis and machine learning
•
Solid SQL skills, comfortable working with large, complex datasets
•
Working knowledge of GCP, particularly BigQuery; familiarity with cloud-based data pipelines
•
Practical experience building lead scoring and churn prediction models
•
Experience with or strong conceptual understanding of Media Mix Modeling (e.g., adstock, saturation curves, Bayesian approaches such as Meridian, Robyn, or PyMC-Marketing is a plus)
•
Good understanding of media and marketing concepts — campaigns, channels, funnels, attribution, and marketing KPIs
•
Ability to communicate technical findings to non-technical stakeholders, including clients
•
Willingness to build expertise in Google Ads Data Hub (ADH), or prior exposure to ADH study types (Frequency Analysis, Brand Lift, Path to Conversion, etc.)
Good to Have:
•
Experience with GA4, Google Ads, Meta Ads, or other marketing platform data
•
Exposure to reverse ETL / audience activation workflows
•
Experience with Looker Studio, Power BI, or similar BI tools
•
Prior experience in a media agency, ad-tech, or martech environment
Qualifications:
•
Bachelor’s/Master’s degree in Statistics, Computer Science, Data Science, Economics, or a related quantitative field
•
2–5 years of relevant experience in data science/analytics roles (adjust per seniority)
Legal
Here at Havas across the group we pride ourselves on being committed to offering equal opportunities to all potential employees and have zero tolerance for discrimination. We are an equal opportunity employer and welcome applicants irrespective of age, sex, race, ethnicity, disability and other factors that have no bearing on an individual’s ability to perform their job
Contract Type :
Permanent
Here at Havas across the group we pride ourselves on being committed to offering equal opportunities to all potential employees and have zero tolerance for discrimination. We are an equal opportunity employer and welcome applicants irrespective of age, sex, race, ethnicity, disability and other factors that have no bearing on an individual’s ability to perform their job.