Data Science Researcher (Part-Time 25%)

Rubrik
Tel Aviv, IsraelPosted 24 February 2026

Job Description

<h2><strong>Data Science Researcher (Part-Time 25%)</strong></h2> <p><strong>Team:</strong> Data Research Team </p> <p><strong>Time Commitment:</strong> 25% (approx. 1 day a week)</p> <p><strong>Location: </strong>Tel Aviv, Israel</p> <h3><strong>About the Role</strong></h3> <p>We are seeking an advanced PhD Candidate to join our Data Research team as a part-time researcher and subject matter expert. The core team is responsible for building and shipping data science algorithms for Rubrik’s product line, with a special emphasis on Cyber Security.</p> <p>We are opening this specialized role to tackle longer-term, high-complexity research initiatives that require deep academic rigor. You will focus on bringing State-of-the-Art methodologies, with an emphasis in LLMs and Advanced NLP, into our ecosystem.</p> <p>This role is designed for a researcher who is "hands-on." We value deep theoretical knowledge, but we require the ability to translate that theory into productive, working code within a limited timeframe.</p> <h3><strong>What you’ll be doing</strong></h3> <ul> <li><strong>Long-Horizon Research:</strong> Lead specific, deep-dive research initiatives that require advanced methodology (e.g., novel anomaly detection architectures or LLM-based reasoning for security threats) without the pressure of daily sprint cycles.</li> <li><strong>LLM Innovation:</strong> Design and prototype advanced LLM workflows (RAG, Agents, Fine-tuning) to solve specific security challenges that standard APIs cannot handle.</li> <li><strong>Academic-to-Industry Bridge:</strong> Act as a knowledge hub for the team; bring SOTA academic concepts, recent paper findings, and novel techniques into the team’s toolkit.</li> <li><strong>High-Impact Prototyping:</strong> Build functional Proofs of Concept (POCs) that the full-time engineering team can eventually operationalize.</li> </ul> <h3><strong>Qualifications</strong></h3> <p><strong>Required:</strong></p> <ul> <li><strong>Current enrollment in a PhD program</strong> (Mathematics, Computer Science, Statistics, or related field) with a focus on Machine Learning, NLP, or AI.</li> <li><strong>Previous industry experience</strong> (internships or full-time) demonstrating the ability to work with noisy, real-world data.</li> <li><strong>Deep Practical Engineering:</strong> Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, Hugging Face).</li> <li><strong>LLM Expertise:</strong> Demonstrated experience working with Transformers and LLMs beyond simple prompting (e.g., experience with embeddings, vector databases, quantization, or fine-tuning).</li> <li><strong>Self-Starter:</strong> Proven ability to manage research projects independently with minimal supervision.</li> <li><strong>Communication:</strong> Excellent ability to explain complex mathematical concepts to engineers and stakeholders (English/Hebrew).</li> </ul> <p><strong>Preferred:</strong></p> <ul> <li>A track record of publications in top-tier conferences (NeurIPS, ICML, ICLR, ACL, etc.).</li> <li>Background or strong interest in Cyber Security.</li> <li>Experience with cloud environments (AWS/Azure/GCP) and distributed data tools (Spark/Databricks).</li> </ul><div class="content-conclusion"><h2>Join Us in Securing the World's Data</h2> <p>Rubrik (RBRK), the Security and AI Operations Company, leads at the intersection of data protection, cyber resilience, and enterprise AI acceleration. Rubrik Security Cloud delivers complete cyber resilience by securing, monitoring, and recovering data, identities, and workloads across clouds. Rubrik Agent Cloud accelerates trusted AI agent deployments at scale by monitoring and auditing agentic actions, enforcing real-time guardrails, fine-tuning for accuracy and undoing agentic mistakes. </p> <p><a href="https://www.linkedin.com/company/rubrik-inc/mycompany/verification/">Linkedin</a> | <a href="https://twitter.com/rubrikinc">X (formerly Twitter)</a> | <a href="https://www.instagram.com/r ... (truncated, view full listing at source)
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