Data Scientist (AI)

TL;DR

Data Scientist (Python/AI): Deliver end-to-end data science projects using classical ML and deep learning with an accent on tabular and time-series data. Focus on building predictive models, collaborating with business stakeholders, and shaping the company's Data Science practice.

Location: Remote (Must be based in Colombia, Argentina, or Brazil)

Company

AI-native consulting and technology services firm specializing in enterprise transformation across cloud, data, and software engineering.

What you will do

• Deliver end-to-end data science projects using classical ML and deep learning from exploration to deployment and tracking.
• Collaborate with business stakeholders to identify opportunities and translate them into measurable data-driven solutions.
• Present complex analytical findings in an actionable way to both technical and non-technical audiences.
• Support presales activities by preparing solution concepts and estimating project scope and value.
• Contribute to the strategic development and recruitment initiatives of the Data Science practice.

Requirements

• Proven experience delivering end-to-end DS projects, including EDA and A/B testing.
• Strong expertise in tabular and time-series data, feature engineering, and predictive modeling.
• Proficiency in Python and libraries such as pandas, scikit-learn, TensorFlow, or PyTorch.
• Experience leading or mentoring analytics teams and coordinating with business stakeholders.
• Fluency in English for meetings with international clients.
• Must be based in Colombia, Argentina, or Brazil.

Nice to have

• Hands-on experience with generative AI, computer vision, or deep learning projects.
• Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools.
• Experience with data visualization or BI tools for communicating insights.

Culture & Benefits

• Opportunity to work on real-world AI-driven projects across diverse industries.
• Access to a global team with opportunities for collaboration across continents.
• Inclusive environment prioritizing continuous learning, innovation, and ethical AI standards.