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Lead Data Scientist

Data Scientist Full-time Permanent LATAM

Job details

Not specified Salary
LATAM Eligibility
Mid-Senior Level Experience
Full-time Employment

About this role

Role overview

Lead Data Scientist role operating remotely within Latin America, embedded in an AI Engineering and Science practice that serves marketing and advertising clients. The position involves leading data science workstreams end-to-end, from problem framing through modeling, deployment, and measurable client impact. It sits at the lead analyst level and is suited to an experienced practitioner who can both deliver hands-on analytical work and guide others on the team.

Responsibilities

- Lead the design, development, and deployment of advanced analytics and machine learning solutions for marketing and advertising use cases. - Translate ambiguous business questions into structured analytical approaches, data requirements, and measurable outcomes. - Build, validate, and productionize statistical and machine learning models, ensuring robustness, interpretability, and performance. - Collaborate with engineering and client-facing teams to integrate models into production pipelines and reporting environments. - Communicate findings, methodology, and recommendations to technical and non-technical stakeholders. - Mentor junior data scientists and contribute to internal best practices, code quality, and reusable modeling standards.

Requirements

- Significant experience as a hands-on data scientist delivering production-grade machine learning solutions. - Strong proficiency in Python or R, SQL, and common ML frameworks, with solid grounding in statistics and experimental design. - Experience working with marketing, advertising, or customer analytics datasets such as campaign performance, attribution, or audience segmentation. - Demonstrated ability to lead projects, manage stakeholders, and present technical work to business audiences. - Comfortable operating remotely and collaborating across distributed teams in Latin America.

Nice to have

- Familiarity with cloud data platforms and MLOps tooling for model deployment and monitoring. - Exposure to generative AI, NLP, or recommendation systems used in marketing contexts.

Skills detected in the listing

PythonSQL
Detected Sep 25, 2026
Last verified Sep 25, 2026

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