דרושים » דאטה » Senior Data Scientist

As a Machine Learning Scientist, you will design, build, and deploy advanced models that guide pricing and promotional optimization across us. You will work closely with other scientists, engineers, analysts, and product teams to translate complex business challenges into scalable, data-driven solutions that deliver measurable impact.

Key Job Responsibilities and Duties:

Develop and deploy models for causal inference, uplift estimation, and optimization to measure and maximize the incremental effect of price and promotion decisions.

Design and improve dynamic pricing algorithms that balance competitiveness, conversion, and profitability.

Contribute to the development of platform capabilities, enhancing experimentation, simulation, and decision-support capabilities.

Partner with product and business stakeholders to translate scientific insights into actionable strategies.

Stay up to date with the latest advances in machine learning, causal modeling, and pricing optimization, and apply them pragmatically at scale.

As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new AI-based defense techniques against cyber-threats. You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin, shaping the future of cybersecurity and impacting millions of customers.
Key Responsibilities
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

We are looking for an experienced Applied AI/ML Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform, designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

We are looking for an experienced Applied Data Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform - designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops - enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productionize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

We're looking for a Senior Data Scientist to join the AI cybersecurity team in the Security and Networking Architecture group. As a Senior Data Scientist youll have the opportunity to take an active part in the research and development of our world-class networking and data center security products. This role involves creative problem solving alongside engineering teams, and is key for the continued success of AI networking security.

What youll be doing:

Developing agentic AI systems for security, combining generative models, RAG, and tool-augmented reasoning to automate threat analysis and response workflows.

Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Developing, implementing and improving models and algorithms across media types, whether time series, images, text, audio or video.

Leveraging data pipelines to efficiently process and transform large volumes of data for training and inference purposes.

Applying alignment techniques and parameter efficient fine-tuning to improve model performance.

Measuring and benchmarking model and application performance to drive improvements.

Driving the gathering, building, and annotation of domain specific datasets for benchmarking and training.

Collaborating closely with software and hardware engineers on new features and improvements. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

We are looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through our companys SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.
This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.
Key Responsibilities
Lead the design, development, and deployment of AI/ML models that enhance our companys security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals.

We're looking for a Senior Car Insurance Pricing Expert to help shape how we price risk across our global business, from our Tel Aviv office.
This isn't a traditional actuarial role. You'll sit at the intersection of Insurance, Data Science, Product, Engineering, and Business Strategy on our Insurance team, owning hard pricing and risk-management problems end to end. That means finding opportunities, designing better approaches, building scalable tools with technical teams, and turning insights into decisions that move growth, profitability, and risk selection forward.
You might be a trained actuary, a pricing leader, a decision scientist, or a technically strong insurance operator who's built serious pricing capabilities. Formal credentials are a plus, but they're not the point. The point is whether you can use data, insurance intuition, statistical rigor, and AI-enabled tools to solve complex pricing problems better and faster than the industry standard.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Own and evolve core components of Car pricing strategy, bringing analytical rigor and product-minded creativity to how we price risk
Identify high-leverage opportunities across rating, underwriting, segmentation, risk selection, growth, profitability, and portfolio management
Build, evaluate, and improve Car pricing and risk models using actuarial methods, machine learning, AI-enabled workflows, and strong business judgment
Partner with Data Science, Product, Engineering, Finance, and Growth to turn pricing ideas into scalable capabilities
Translate complex pricing problems into clear product and platform requirements, helping teams build internal tools that make better decisions faster
Define and track key metrics - loss ratio, rate adequacy, conversion, retention, segmentation lift, and model performance - to keep decisions grounded in real impact
Make complex actuarial and pricing concepts clear and actionable for technical and non-technical audiences alike, and help build pricing acumen across the Tel Aviv team

The Data Science role is the engine behind our industry-leading Exposure Management (EM) platform.
You will be responsible for the AI models that power our CAASM (Cyber Asset Attack Surface Management) capabilities and our advanced Vulnerability Prioritization and Remediation engines.

We are building the intelligence layer that helps organizations implement a Continuous Threat Exposure Management (CTEM) framework. You will build models that normalize fragmented data from hundreds of sources, calculate complex risk scores, and prioritize which exposures actually pose a threat to the business.

We are looking for an experienced and creative data scientist, with a software development touch, to join our Data Science and our family. A data scientist that understands and loves data, and lots of it.

What you will do...
Solve Applied Product Challenges: Deep-dive into our product ecosystem to identify and solve high-impact problems. You will translate complex customer needs into scalable ML features that directly improve the user experience.
Lead Exposure Intelligence R&D: Develop features that unify asset data (CAASM) with threat intelligence. This includes building models for entity resolution (deduplicating assets across fragmented sources) and automated risk assessment.
Advanced NLP & Knowledge Extraction: Use NLP and LLMs to parse unstructured security data-such as CVEs, threat intel feeds, and security advisories-to automate the mapping of vulnerabilities to specific business contexts.
Predictive Prioritization: Design and optimize algorithms that go beyond static CVSS scores. You will incorporate exploitability (EPSS), reachability, and business criticality to help clients focus on the 1% of exposures that matter most.
End-to-End Ownership: Work closely with Product Managers and Data analysts and Engineers to ensure your models aren't just accurate in a notebook, but are robust, explainable, and deliver clear value within the product UI.
Graph-Based Attack Surface Mapping: Identify hidden patterns and relationships between assets, users, and vulnerabilities to visualize the potential "blast radius" of a security gap.

Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.

This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.

Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.

This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.

Responsibilities
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights.
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes.
Work closely with product and engineering teams to translate business needs into scalable AI solutions.
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products.
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance.
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration.
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring.
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration.
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact.

We are seeking a highly skilled Senior Data Scientist to join our dynamic AI team. The ideal candidate blends a strong foundation in machine learning, statistics, and software engineering with a passion for modern, AI-accelerated development. You will be responsible for leading the research, design, and end-to-end development of cutting-edge machine learning systems at scale.
What you'll be doing:
Innovate at Scale: Design and deploy advanced ML solutions by leveraging our vast, large-scale datasets.
Build & Scale: Develop online, scalable models and tools using machine learning, deep learning, NLP, and modern LLM frameworks.
End-to-End Ownership: Drive projects through their entire lifecycle-from translating complex business questions into technical strategies, all the way to robust production deployment.
Production Excellence: Champion high engineering standards by building, monitoring, and optimizing resilient production workflows.
Cross-Functional Collaboration: Work closely alongside data scientists, ML engineers, product managers, analysts, and developers to solve complex, multi-faceted problems.