Data Scientist – AI Research

Job not on LinkedIn

🕒 August 21

🇮🇱 Israel – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 48%

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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Earnix

WebsiteLinkedInAll Job Openings

201 - 500 employees

💳 Fintech

🛡️ Insurance

🏦 Banking

Fintech • Insurance • Banking

Earnix is a global provider of Intelligent Insurance and Banking Operations, focusing on agile, composable, and real-time solutions. The company specializes in predictive analytics, pricing, risk analysis and modeling, customer lifetime value, financial service product design, banking and insurance analytics, personalization, and digital transformation.

📋 Description

• Lead targeted research projects from initial hypothesis through production-ready solutions • Own research deliverable performance and partner with engineering on scalable integration • Research LLMs, agentic systems, and modern AI methods • Design and build AI workflows for integration into the company ecosystem • Establish and contribute to rigorous LLM evaluation frameworks for accuracy, safety, and business alignment • Bridge data, engineering, and product teams • Work with developers to integrate machine-learning features into the core product • Advocate for emerging AI research and methodologies • Read, experiment with, and implement state-of-the-art techniques to advance the research agenda

🎯 Requirements

• 3 to 5 years of proven industry experience as an AI Researcher or Data Scientist • M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a closely related quantitative field • Deep theoretical knowledge and hands-on experience with classical machine learning algorithms and advanced statistical modeling • Experience with RAG pipelines, agentic workflows, autonomous AI systems, and rigorous LLM evaluation mechanisms • Experience with AI productivity and development tools such as Claude Code, Cursor, GitHub Copilot, and advanced prompting frameworks • Ability to independently learn new concepts and proactively research, test, and propose state-of-the-art solutions • Ability to communicate complex mathematical and technical concepts to non-technical stakeholders and collaborate with Engineering • Familiarity with or experience in the Finance domain is advantageous • Knowledge and practical experience with causal inference techniques is advantageous • Experience designing and training deep neural networks using tools such as PyTorch or TensorFlow is advantageous

🏖️ Benefits

• Autonomy to execute key research initiatives and contribute directly to the product roadmap • Resources and mandate to work with the latest GenAI models and frameworks • Collaborative team culture without corporate bureaucracy