Principal Data Scientist, Recommendations

This is a fully remote position, open to applicants in Colombia, +2 more countries.

📋 Description

• Develop recommendation systems that pinpoint potential causes of underperformance, suggest innovative enhancements, prioritize adjustments, and facilitate testing.

• Create intelligent systems that integrate visual, textual, audio, structural, platform, and performance data.

• Convert multimodal signals into diagnostics, scoring systems, recommendations, and decision-support tools.

• Work with video, images, text, audio, metadata, and KPI data utilizing computer vision, embeddings, LLMs, classification, clustering, and multimodal reasoning.

• Design experiments, quantify uncertainty, and differentiate between signal and noise through causal inference, hypothesis testing, regression, matched cohorts, and treatment/control analysis.

• Write Python and SQL for data products, APIs, model pipelines, evaluation frameworks, and internal tools.

• Collaborate with Engineering, Data Engineering, and DevOps to create reliable, observable, scalable, and maintainable systems.

• Enhance training pipelines, feature stores, model serving, evaluation harnesses, and deployment workflows across AWS and GCP / Vertex AI.

• Act as a technical leader and communicate complex AI, machine learning, and measurement concepts to cross-functional teams.

• Assist the organization in adopting superior tools, automation, evaluation methods, and AI-enhanced development practices.

⛳️ Requirements

• PhD in Computer Science is highly preferred; candidates with a PhD in statistics, mathematics, natural science, engineering, operations research/management science, or economics are valued if they possess strong CS and engineering experience; exceptional MS candidates with significant applied AI/ML experience will also be considered.

• 10+ years of experience in applied data science, machine learning, or AI product development, or 5+ years post-PhD in a highly technical applied role.

• Proficiency in production-quality Python.

• Experience in designing data systems, understanding architecture, and collaborating with engineers on deployed data products.

• Ability to extract insights from large data tables and manipulate data using SQL queries and scripting languages.

• Practical experience with Databricks, BigQuery, Flink, or other large-scale data platforms.

• Familiarity with model training, evaluation, deployment, monitoring, retraining, feature pipelines, experiment tracking, model registries, and ML observability.

• Strong knowledge of supervised and unsupervised learning, model evaluation, feature engineering, embeddings, retrieval, ranking, clustering, classification, recommendation systems, and statistical validation.

• Hands-on experience with computer vision, video/image understanding, LLMs, foundation-model workflows, or other applied GenAI systems.

• Strong understanding of probability, statistics, optimization, experimental design, causal inference, hypothesis testing, confidence intervals, and treatment/control design.

• Experience applying models to achieve real business outcomes.

• Excellent written and verbal English communication skills.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health benefits including medical, dental, and vision coverage.

• Flexible working hours and remote work options.

• Generous vacation and paid time off policies.

• Opportunities for professional development and continuous learning.