Principal Data Scientist, Recommendations

🔥 12 hours ago

🌐 Colombia, Chile, +1 more countries – Remote

🇨🇴 Colombia – Remote 🇨🇱 Chile – Remote 🇧🇷 Brazil – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Vidmob

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📣 Marketing

Consulting • Marketing • Advertising

Vidmob is a company specializing in creative data analytics, offering robust tools and solutions to brand teams, creative teams, media teams, and agencies. The company leverages over 40 proprietary AI models and analyzes trillions of creative elements to improve creative and media decisions. Vidmob provides services like creative scoring, creative analytics, and exports, along with Diversity Measurement and GenAI integration. It partners with major ad platforms to enhance creative effectiveness and media ROI, helping brands to achieve better performance metrics such as increased Click-Through Rates and View-Through Rates. Vidmob is recognized by several prestigious awards for innovation and creativity in advertising and media.

📋 Description

• Build recommendation systems that identify likely drivers of underperformance, recommend creative improvements, prioritize edits, and support testing • Develop creative intelligence systems connecting visual, text, audio, structural, platform, and performance data • Turn multimodal signals into diagnostics, scores, recommendations, and decision-support tools • Work with video, image, text, audio, metadata, and KPI data using computer vision, embeddings, LLMs, classification, clustering, and multimodal reasoning • Design experiments, quantify uncertainty, and separate signal from noise using 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 • Partner with Engineering, Data Engineering, and DevOps on reliable, observable, scalable, and maintainable systems • Improve training pipelines, feature stores, model serving, evaluation harnesses, and deployment workflows across AWS and GCP / Vertex AI • Serve as a technical leader and explain complex AI, machine learning, and measurement concepts to cross-functional teams • Help the organization adopt better tools, automation, evaluation methods, and AI-assisted development practices

🎯 Requirements

• PhD in Computer Science strongly preferred; PhD in statistics, mathematics, natural science, engineering, operations research / management science, or economics valued with strong CS and engineering experience; exceptional MS candidates considered with substantial applied AI / ML experience • 10+ years in applied data science, machine learning, or AI product development, or 5+ years post-PhD in a highly technical applied role • Production-quality Python • Experience designing data systems, reasoning about architecture, and partnering with engineers on deployed data products • Ability to extract information from large data tables and manipulate data using SQL queries and scripting code • Hands-on experience with Databricks, BigQuery, Flink, or similar large-scale data platforms • Experience with model training, evaluation, deployment, monitoring, retraining, feature pipelines, experiment tracking, model registries, and ML observability • Strong command of supervised and unsupervised learning, model evaluation, feature engineering, embeddings, retrieval, ranking, clustering, classification, recommendation systems, and statistical validation • Practical experience with computer vision, video/image understanding, LLMs, foundation-model workflows, or other applied GenAI systems • Strong command of probability, statistics, optimization, experimental design, causal inference, hypothesis testing, confidence intervals, and treatment/control design • Experience applying models to real business outcomes • Strong written and spoken English skills