As a data scientist, 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 our business. Together with other Data Engineers and Product Managers, you will translate the voice of our customer into best-in-class digital insights.

Responsibilities:
Analyzing data from various sources and transforming it into actionable insights that directly drive business growth.
Building machine learning algorithms for bidding - using classification and clustering to optimize campaign performance.
Leveraging artificial intelligence (GenAI) techniques to query data for intelligent insights and automated decision-making processes, unlocking hidden value from data.
Leading tasks from exploration to proof of concept (POC) and ensuring smooth transitions to scalable production environments.
Collaborating with data engineers and product managers to ensure the delivery of high-quality production results.
Creating and owning key metrics while developing new models and capabilities for innovative product solutions.
Optimizing scalability and ensuring the performance of data pipelines and ML models, handling large-scale, dynamic datasets.

Were looking for a Data Scientist Expert to join us and spread the power. In this role, you will lead the next generation of Data Security Posture Management (DSPM) and Secret Detection. You will build the algorithmic engines that discover and protect the world's most sensitive information in the cloud, driving R&D initiatives to implement AI-driven solutions that tackle emerging threats and enhance our customers' security posture.
WHAT YOULL DO
Lead applied research for AI-driven features in our DSPM and Secret Detection domains
Conduct deep research and classification of sensitive data (PII, secrets) across complex structured and unstructured formats
Own the research lifecycle from raw data exploration and failure analysis to production-grade implementation
Identify and assess data security risks and use cases within cloud environments
Leverage LLMs to automate complex security research and enhance data classification at scale
Partner with Engineering, Security Research, and Product teams to define research goals and maintain production pipelines
Evaluate and optimize AI models and algorithms using real-world datasets to ensure high accuracy and scalability.

Required Machine Learning Scientist II - GenAI models and applications
21539
Role Description
Leadership/Team Quote:
The Content Intelligence team builds the platform that processes millions of images and texts daily, enriching our catalog with advanced machine learning models for content understanding, classification, and personalization. These capabilities power smarter recommendations, improved search experiences, and intelligent chatbots and agents that enhance customer interactions. The team also plays a key role in the AI Trip Planner, a new Generative AI-driven project transforming how travelers plan their next vacation
Role Description:
As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
Key Job Responsibilities and Duties:
Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning), build algorithms, and engineering approaches to drive business impact..
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate models performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

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 our 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 an AI Solutions Engineer, youll partner with enterprise clients to understand their challenges and architect AI-driven solutions using the platform. Youll collaborate with leading data science and ML engineering teams, working alongside experienced practitioners to ensure smooth adoption and measurable business outcomes.

Youll design and deliver proofs of concept, lead workshops, and build compelling demos showcasing the capabilities of for AI evaluation, monitoring, and reliability. Acting as the key interface between our product, research, and customer teams, youll help translate technical requirements into impactful AI solutions.

Were looking for a talented and driven Data Science to join our Data Science / Applied AI team in Tel Aviv.
Youll work alongside senior data scientists and ML engineers on production AI systems that directly impact clinical care.

This is a hands-on role. Youll contribute to real projects from day one: improving AI-powered services, building evaluation pipelines, working on data quality and processing, and supporting the infrastructure that keeps our systems running reliably at scale. We value people who can operate independently, learn quickly, and deliver quality work in a fast-moving environment.

Responsibilities
Contribute to our production AI services (Python)
Build and maintain evaluation frameworks and data pipelines
Conduct data analysis to support research, quality validation, and product decisions
Support model integration and deployment workflows
Collaborate with DevOps, QA, and Product teams on cross-functional deliverables
Document technical work and share knowledge with the team

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within our company to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with our company and we remain a trusted partner.
The gTech Ads Data Science EMEA team helps measure and optimize marketing ROI for our companys largest clients. We build bespoke models that address clients key business issues.
In this role, you will be responsible for applying best data science practices to solve our ads customers problems in marketing. You will be passionate about bringing the best of our companys Machine Learning (ML) capabilities to build solutions that address our customer's problem-space. You will be responsible for executing on gTechs strategy and goal to deliver applied data science to our company's largest ads customers.
Responsibilities
Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with Machine Learning and statistics.
Collaborate with customers to unpack their problems and identify the best statistical techniques that can solve the problem; own the development of a modeling framework.
Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a larger solution, collaborate with Product/Engineering teams to increase and optimize capabilities of our data scientist (DS) team, employing methods which create opportunities for scale, proactively helping to drive innovation.
Work with customer and internal teams to translate data and model results into tactical and insights that are actionable for decision.
Develop comprehensive understanding of our company data structures, and metrics, advocating for product changes where needed.

We are seeking for a talented Data Science Team Lead to join our development center in Israel, a fast-paced and innovative environment. You are a passionate data professional with proven experience in building and growing high-quality data teams, which will play a pivotal role in driving the execution and delivery of advanced Machine Learning models and algorithms, through mentorship and hands-on development, and by working closely with clients to understand their needs and key objectives.
Responsibilities :
Serve as a team expert in the most advanced Machine Learning methodologies, helping to plan and implement successful and impactful data science projects
Manage experienced team of data scientists, providing career guidance and performance evaluation to develop and retain talent
Solve non-routine analysis problems based on high-dimensional, complex data sets, by actively mentoring and coding
Lead deployment of large-scale data pipelines, ensuring a seamless delivery
working directly with key client executive decision makers and acting as the leading expert for best-practice data-driven solutions
Establish strong cross-functional relationships throughout the organization to improve our customer experience and set of offered skills.

The Growth and Notifications (GaNT) Data Science team's mission is to deliver the best of 's products to our users by enabling high-quality notifications and driving growth across the ecosystem. We are a team of data scientists and analysts who work to embed a deep, empirical understanding of user behavior into the product development lifecycle. This enables our product partners to take smarter risks and build more engaging, high-quality experiences that drive sustainable growth.
We are part of the broader Ecosystem Growth (EG) Data Science team within our company Identity and Engagement (GIE). Our work is pivotal in increasing the number of users who experience the full value of our company.
This is an exciting opportunity to join a team that is at the forefront of driving user engagement and ecosystem growth at our company.
Responsibilities
Lead large-scale data analysis and novel modeling approaches to create a deep understanding of user behavior with notifications and proactive agentic experiences.
Partner with Product, Engineering, and UX research to define and develop novel evaluation metrics, validation methodologies, and experimentation frameworks for proactive quality models and AI-driven notification agents.
Provide analytical thought leadership and advanced statistical expertise on user journeys, engagement models, and long-term causal effects across the GIE and our company ecosystem.
Translate complex findings into actionable product recommendations, effectively presenting to cross-functional stakeholders at all levels to influence the product roadmap.
Define, implement, and own key metrics to measure the quality, impact, and value of notifications and user-state models.

Required Fraud Group Manager
Tel Aviv-Yafo, Gush Dan, Israel
We offer the industrys only platform that fuses customer identity and anti-fraud solutions - customer identity management, identity verification, and fraud prevention.
We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.
About the Role:
The Fraud Group Manager leads the professional organization responsible for the "Intelligence Core" of our fraud detection products. You manage three specialized teams-Fraud Data Science, Fraud Research, and Fraud Analytics-that implement the core logic our customers use to fight fraud.
In this role, you aren't just a strategist; you are a Production Owner. You are responsible for the health, observability, and continuous improvement of detection logic in live environments. You work in a high-impact triad with Product Management and Platform Engineering, serving as the bridge between deep technical expertise and the customers who rely on our product to protect their business.
What youll do:
Group Leadership & Customer Engagement
Direct Management: Lead and scale a multidisciplinary organization of Data Scientists, Researchers, and Analysts.
Customer Fronting: Act as the primary technical fraud authority for our customers. You will join high-stakes meetings with CISOs and Fraud Heads to explain our detection logic, address performance concerns, and align our roadmap with their evolving threat landscape.
Stakeholder Orchestration: Partner with Product Management to define the "what" and Platform Engineering to ensure the "how" (infrastructure) meets your group's logic requirements.
Production Ownership & Quality Systems
Detection Observability: Own the end-to-end monitoring and health of fraud detection in production. You ensure that we have the visibility to know if a model is degrading or a specific customers detection is underperforming.
On-Call for Performance: Serve as the escalation point for critical detection failures or sudden spikes in false positives/negatives, ensuring rapid mitigation for impacted customers.
Quality Assurance Framework: Create and maintain a robust quality system (CI/CD for fraud logic) to ensure smooth, ongoing updates to detection models and heuristics without disrupting customer environments.
Lifecycle Management: Oversee the continuous tuning and optimization of live detection logic based on real-world feedback loops.
Technical Execution
Hands-on Vetting: Maintain deep technical fluency. You must be able to review Python code, validate complex SQL queries, and interpret model performance metrics to ensure they meet our high standards.
Logic Governance: Define the schemas and standards for how detection logic is developed, ensuring that research insights are effectively operationalized by the Data Science team.