דרושים » תוכנה » - data Scientist - Leading Media Group - Tel Aviv - Hybrid

we are seeking an experienced and visionary Data Science Team Lead to join our dynamic technology organization.
The successful candidate will lead a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions.
This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, exceptional leadership skills, and a passion for continuous learning and development.
Responsibilities:
Lead, mentor, and develop a team of data scientists both methodologically and technically to deliver high-impact projects aligned with business objectives.
Design, implement, and optimize classic machine learning models to solve complex business problems.
Apply gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs) to create innovative solutions for products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization.

we are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

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.

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 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 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.

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows
Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
Collaborate with engineering teams to design, build, and maintain production pipelines
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

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 an experienced Data Science Manager to lead and grow our Data Science team. This is a managerial role focused on leading a team of Data Scientists while driving the strategy, execution, and delivery of impactful AI and ML initiatives across our SaaS platform.
You will be responsible for both people leadership and technical direction - ensuring high standards of execution, mentoring team members, and aligning data science efforts with product and business goals. This role requires a strong hands-on background combined with proven team management experience.
What You Will Do:
Lead, mentor, and manage a team of 7-10 Data Scientists, fostering a culture of ownership, excellence, and continuous learning.
Own the teams roadmap, prioritization, and delivery of AI initiatives.
Provide technical and architectural guidance across projects.
Drive end-to-end execution of data science solutions - from problem definition and research to modeling, evaluation, deployment, monitoring and enhancement cycles.
Collaborate closely with Product, Engineering, and Business stakeholders to translate business needs into scalable AI solutions.
Ensure production-grade standards, model performance monitoring, and continuous improvement.
Stay up to date with advances in machine learning, GenAI, and LLM technologies, and translate them into business impact.
Take responsibility for hiring, onboarding, and developing top data science talent.

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.

We are looking for an experienced NLP Data Science Team Leader to lead a team of talented NLP Data Scientists and drive the development of cutting-edge NLP solutions at scale. This role combines hands-on technical leadership, people management, and strategic influence over product and research directions.



Responsibilities

Lead and grow a team of NLP Data Scientists
Manage, mentor, and support team members professional development
Foster a culture of excellence, ownership, and continuous learning
Own end-to-end delivery of NLP solutions
Oversee algorithmic features from ideation through research, development, and production
Ensure high-quality, scalable, and maintainable solutions
Drive technical direction and innovation
Guide research efforts and evaluate new NLP/ML technologies
Translate business needs into impactful NLP solutions
Collaborate cross-functionally
Work closely with Product, Engineering, and Business stakeholders
Align team priorities with company goals and product roadmap
Maintain hands-on involvement
Contribute to architecture, modeling, and critical algorithmic challenges
Review code, experiments, and methodologies
Scale impact
Improve processes, workflows, and best practices for research and production
Ensure efficient use of large-scale data and infrastructure

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.