לוח משרות דרושים Data Scientist משרה מלאה

As a Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.

What you will be doing
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.

As a Research Scientist in Model Evaluation, you are the ultimate authority on model quality and utility. You will design the automated judges, reward models, evaluation datasets, and benchmarking ecosystems that determine the future of LTX. Your mission is to provide the "ground truth" for our pre-training and post-training teams. You will blend the rigor of a researcher with the intuition of a product-thinker, developing metrics that capture both the aesthetic soul of a video and the functional precision required for high-stakes professional use.

Key Responsibilities
Steer Training & Research: Systematically evaluate model checkpoints to provide actionable insights that guide training experiments and architectural decisions.
Design Benchmark Ecosystems: Develop and run rigorous benchmarks for release candidates against competitive models, ensuring LTX-2 remains world-class.
Build Next-Gen Metrics: Develop robust automatic metrics and Reward Models (e.g., for RL, ITS, auto-research agents) that quantify complex attributes like temporal coherence, physical correctness, spatial accuracy, and foley synchronization.
Diagnose & Analyze: Perform deep root-cause analysis on model failures, providing the diagnostic clarity needed for researchers to implement targeted fixes.
Scale Evaluation: Collaborate with platform engineers to deploy evaluation frameworks across large-scale GPU clusters.

a palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere.
job description:
as a data Scientist, youll join a team shaping the future of identity security and pioneering research in areas of cybersecurity and agentic ai.
advance your data science career by applying your established expertise to solve complex, real-world problems at scale and drive innovation alongside leaders in the cybersecurity and ai space.
research, design, evaluate and production deployment of advanced ai/ml models, specializing in llms, rag systems, and agentic ai applications.
explore and analyze large-scale datasets to uncover patterns and drive actionable insights.
collaborate closely with product managers, engineers, and analysts to support feature development and validate ml ideas.
stay up to date with the latest academic and industry trends in ai/ml and apply best practices to real-world challenges.
grow your skills in classic Machine Learning, deep learning, Natural Language Processing ( NLP ), llms and cybersecurity applications.

Required Data Scientist
About the Role
The Data Science department plays a pivotal role in our company, generating value to us by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities.

Were looking for a Data Scientist to join our R&D department!
Why is this role so important at our company?
we are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist in our company, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights.
So, what will you be doing all day?
Your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use.

Were looking for a Data Scientist to join our R&D department!
Why is this role so important at our company?
we are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist in our company, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights.
So, what will you be doing all day?
Your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use

We are seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Code Generation and LLMs reasoning with specific focus on reinforcement learning, synthetic data generation and advanced scaffolding/agentic techniques. You will have the opportunity to work with a broad and highly interdisciplinary team of scientists, engineers, and cross-functional partners, and will have access to cutting edge technology, resources, and research facilities.
AI Research Scientist Responsibilities
Lead, collaborate, and execute on research that pushes forward the state of the art in agentic code generation
Work towards long-term ambitious research goals, while identifying intermediate milestones
Directly contribute to experiments, including designing experimental details, implement reusable code, running evaluations, and organizing results
Contribute to publications and open-sourcing efforts
Mentor other team members. Play a significant role in healthy cross-functional collaboration,

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and us. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

Applied Data Scientist
Tel Aviv, Israel (Hybrid On-site)
Full-Time
We are the trust layer backbone for the Generative AI revolution, building the critical testing infrastructure needed to enable the next generation of AI: Agentic Systems. We provide an end-to-end platform that goes beyond simple metrics to evaluate complex, multi-step LLM workflows. Our technology employs a swarm of specialized evaluation agents to validate complex AI workflows and isolate the root cause of errors. We empower organizations to solve the black box problem, ensuring their agents are reliable, safe, and hallucination-free from the first prototype to high-scale production.
About the Role
As an Applied Data Scientist, you will research, design, and implement complex algorithms that assess and monitor AI systems, including cutting-edge LLM applications. You will work in a high-paced environment where impact is key. You will collaborate closely with our engineering and product teams to push the boundaries of what automated AI evaluation can achieve, ensuring our users get the most reliable and actionable insights possible.

We're in search of an exceptional hands-on Data Scientist who can bridge data infrastructure, fraud analytics, and machine learning to enhance our fraud detection capabilities. This role requires someone who can drive projects from ideation to implementation, leading these efforts while thinking strategically about how we detect and prevent fraud at scale. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.

Your Arena

Develop and enhance fraud detection models from concept to production, focusing on data normalization, network analysis, and risk scoring.
Take ownership to identify, analyze, and implement solutions for fraud patterns and behavioral anomalies.
Design, build and maintain data science pipelines and fraud intelligence systems to improve detection accuracy.
Collaborate with product, engineering, and risk teams to implement fraud prevention strategies.
Own projects end-to-end - balancing short-term wins with long-term strategy.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.
As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.
You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.
What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in our companys search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of our companys AI platform. Develop models and framework solutions for the group.