Senior Data Scientist: Causal ML & Analytics Leader

Publicis Groupe ANZ; Bogotá; Presencial; COP 9.000.000 - 12.000.000; Jornada completa

Descripción de la vacante

Publicis Global Delivery in Bogotá is seeking a data scientist to apply data science and machine learning, with a strong focus on causal inference and statistics, to generate actionable insights for campaign planning, measurement, and optimization.

You will build and maintain scalable data pipelines and analytical models, summarize and communicate results to technical and non-technical audiences, lead projects with minimal supervision, develop ML models and SQL analyses, and design AI/data

Formación

• Strong data science and ML expertise.
• Expertise in causal inference and statistics.
• Advanced SQL proficiency.
• Python proficiency.
• Experience with Google Cloud Platform services (BigQuery, Data Studio/Looker Studio, Dataproc).
• Experience with econometric models and ML methodologies.
• Ability to independently lead projects and work with minimal coaching.

Responsabilidades

• Build, test, and maintain scalable data pipelines and analytical models.
• Summarize, visualize, communicate, and document analytics concepts, processes, and results for both technical and non-technical audiences.
• Collaborate with team members, stakeholders, and occasionally clients to define analytical objectives, approaches, and timelines.
• Lead projects with minimal oversight, establish expectations, ask the right questions, create project plans, and execute them independently.
• Develop machine learning models, perform SQL-based analysis, and contribute to automation initiatives.
• Design and automate AI/data pipelines that support recurring reporting, data transformation, prediction, measurement, and dashboarding workflows.

Conocimientos

Data Science

Machine Learning

Causal inference

SQL

Python

GCP (BigQuery)

Herramientas

BigQuery

Data Studio/Looker Studio

Dataproc

Descripción del empleo

Publicis Global Delivery in Bogotá is seeking a data scientist to apply data science and machine learning, with a strong focus on causal inference and statistics, to generate actionable insights for campaign planning, measurement, and optimization.

You will build and maintain scalable data pipelines and analytical models, summarize and communicate results to technical and non-technical audiences, lead projects with minimal supervision, develop ML models and SQL analyses, and design AI/data