Cloud Data Scientist – Havas CSA
Location: Perú Fully Remote.
CSA, the data consultancy within Havas Media Group and part of the Havas Center of Excellence team, is seeking a Cloud Data Scientist to design, develop, and deploy the advanced machine learning models that fuel our data-driven decision-making.
You will leverage your expertise in Google Cloud Platform, Python, SQL, and statistical modeling to create predictive and scalable AI solutions. Your work will directly impact the intelligence and capabilities of our products, empowering teams across the organization to extract valuable predictive insights.

What you’ll do:
Design, develop, and deploy scalable ML models on Google Cloud Platform.
Ensure model accuracy, fairness, and robustness throughout the lifecycle.
Implement and customize open-source MMM frameworks, such as Google Meridian or Meta Robyn, to align with client’s specific business requirements and datasets.
Design and implement statistical experiments (A/B testing) for optimal product and feature evaluation.




Collaborate with data engineers and marketing managers to understand their requirements and provide analytical solutions
Build, run, and customize Marketing Mix Models (MMMs) for media optimization.
Extract and analyze data using advanced SQL (BigQuery) and Python for ML.
Implement and manage MLOps for model monitoring and incident resolution.
Develop custom Python applications to automate model training and deployment processes.
Document ML processes comprehensively and practice collaborative Git-based development.

What you’ll bring:
Essential Qualifications:
Excellent verbal and written English communication skills are required.
3+years of proven hands-on experience with Google Cloud Platform (GCP) and its AI/data services (Vertex AI, BigQuery).
Strong SQL proficiency, particularly with BigQuery SQL for large datasets.
Expertise in Python programming, with extensive experience in machine learning and data science libraries.
Demonstrated expe

📌 Cloud Data Scientist (Lima)
🏢 Havas Perú
📍 Lima