לוח משרות דרושים Data Scientist משרה מלאה

We are looking for a highly capable and experienced Data Scientist to lead and develop advanced deep learning solutions for metrology challenges within our CTO group.
Responsibilities
What you will be doing:
Lead feasibility studies and proof-of-concept investigations for advanced deep learning solutions addressing complex metrology challenges.
Design, develop, and evaluate deep learning infrastructure for early-stage metrology technologies.
Propose and drive new deep learning directions, research ideas, and innovative approaches in collaboration with the CTO group.
Work closely with multidisciplinary teams to translate research concepts into practical metrology solutions.
Stay up to date with state-of-the-art deep learning methods and apply them to novel semiconductor metrology problems.

Job Description Summary:
Apply strategic and data analytics skills to solve problems for the company Risk team. Work with stakeholders across different teams such as Product, Platform, Machine Learning, Operations to drive strategic initiatives. The Global Risk Automation Strategy (GRAS) team focuses on driving automation initiatives for the risk back office. We work closely with the Front end strategy, consumer and seller risk operations, product, and modeling teams to identify automation opportunities to drive efficiency.
Job Description:
As a Decision Scientist you will apply your strategic and analytical skills to solve challenging business problems. You will team up with world-class professionals to identify actionable insights that ultimately impact the bottom line of the company. We work in a space that looks deeply into emerging fraud trends to come up with analytical solutions to fight these fraud trends and we also work on business enablement opportunities that fuel growth and drive efficiencies within the organization.

We are looking for an experienced Product Manager to lead Diagnosis Insights domain - responsible for the intelligence layer that powers our clinical suggestions and diagnosis capture experience across patient populations.
This role sits at the intersection of clinical reasoning, data, and AI. You will define, refine, and scale the logic behind diagnosis insights - owning the end-to-end experience from medical modeling through how suggestions are surfaced to clinicians and others. Your mission is to drive superior accuracy, broad coverage, and measurable impact across patient types and care models.
This position is ideal for a PM who combines strong analytical and technical depth with clinical intuition, and who is excited to build AI-powered products that influence real-world clinical decisions at scale.
Responsibilities:
Define and drive the product roadmap for Diagnosis Insights domain. Own the long-term vision for diagnosis suggestion ecosystem - from medical logic and model strategy to how insights are presented, prioritized, and acted upon by clinicians.
Own and define KPIs, including model coverage and precision, alongside end-user adoption metrics (e.g., physician address rate).
Lead core product interfaces: Own the insights experience on both the physician and administrative teams' interfaces.
Work closely with Engineering, Data Scientists, Medical Experts while actively engaging with clients and end users to deeply understand their desired outcomes, and validate new ways to improve our suggestion algorithm.
Translate customer and business requirements into PRDs, technical specifications, and logical flows for the Engine and Core teams.
Explain complex medical logic in simple, non-technical language to internal stakeholders (Support, CSM, Implementation teams) and support generate internal product documentation.
Use SQL and analytical skills to interrogate data, evaluate logic performance, and validate improvements.
Own and manage the product backlog, prioritizing requests based on customer impact, business goals, and urgency.

We are looking for a visionary and technically versatile Data Science Manager to join the Data Science & MLE group within our DS & Analytics organization.
In this pivotal role, you will lead a hybrid team of Data Scientists and Machine Learning Engineers, acting as the bridge between cutting-edge technical innovation and high-level business strategy. You won't just be managing a team; you will be the Technical Lead defining how we solve complex problems-from predicting player behavior to optimizing marketing budgets using the latest in Generative AI.
You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.
Key Responsibilities:
Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.

Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.
Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.
Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.
Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.

As a Research Engineer , you will design, develop, and implement algorithms and models that will enhance the products capabilities, performance, reliability, and scalability. Together with our algo and engineering team members, you will work closely with our product team members to implement algorithms that can be used to drive our business forward as well as the frontier of software development AI technologies.

Responsibilities:

Design, develop, implement and test algorithms and AI-empowered solutions for various product features and applications
Collaborate with cross-functional teams to understand business needs and translate them into algorithmic solutions
Perform research on emerging trends, algorithms, and cutting-edge technologies, and identify ways to incorporate them into our products pragmatically
Propose new and innovative solutions to complex problems and lead the development of algorithms in those areas
Design, cleanse, and utilize benchmarks throughout the process of the algorithm development

Apply strategic and data analytics skills to solve problems for the company Risk team. Work with stakeholders across different teams such as Product, Platform, Machine Learning, Operations to drive strategic initiatives. The Global Risk Automation Strategy (GRAS) team focuses on driving automation initiatives for the risk back office. We work closely with the Front end strategy, consumer and seller risk operations, product, and modeling teams to identify automation opportunities to drive efficiency.
Job Description:
As a Decision Scientist you will apply your strategic and analytical skills to solve challenging business problems. You will team up with world-class professionals to identify actionable insights that ultimately impact the bottom line of the company. We work in a space that looks deeply into emerging fraud trends to come up with analytical solutions to fight these fraud trends and we also work on business enablement opportunities that fuel growth and drive efficiencies within the organization
For the majority of employees, our company's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the company office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.
Job Description:
Essential Responsibilities:
Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.

We are looking for a Data & AI Project Manager to lead the delivery of AI and Generative AI-based solutions for our clients. In this role, you will own projects end-to-end - from initial scoping and requirements definition through development, deployment, and continuous improvement.
This role is well-suited for a technically oriented project or product manager who enjoys working at the intersection of data, AI, engineering, and business, and who thrives in fast-paced, complex environments.
Responsibilities:
Lead the full lifecycle of AI and data projects, from ideation and design through implementation, deployment, and ongoing optimization.
Translate business and user needs into clear system requirements, technical specifications, and structured delivery plans.
Define project scope, priorities, milestones, and deliverables, ensuring execution on time, within scope, and within budget.
Collaborate closely with development, data, and infrastructure teams to support efficient delivery and resolve technical dependencies.
Drive alignment between technical solutions and business objectives, ensuring delivered solutions generate tangible client value.
Manage multiple stakeholders on both client and internal sides, maintaining clear communication and expectations.
Support the design of intuitive, user-centered AI solutions and workflows.
Identify risks, manage trade-offs, and proactively address challenges throughout the project lifecycle.

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.

about the job
the growth and notifications (gant) data science team's mission is to deliver the best of google'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 google identity and engagement (gie). our work is pivotal in increasing the number of users who experience the full value of google.this is an exciting opportunity to join a team that is at the forefront of driving user engagement and ecosystem growth at google.
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 google 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.

We are looking for a highly technical and innovative, hands-on Data Scientist to join our Threat Research group.

Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for new products, and drive innovation and thought leadership in cybersecurity.

Key Responsibilities:

Lead and contribute to the development, evaluation, and deployment of machine learning, deep learning, and large language models (LLMs) for cybersecurity applications.

Drive and support data-driven research projects, from ideation and prototyping to production deployment, using both classic ML and advanced deep learning techniques.

Perform comprehensive data collection, preprocessing, analysis, and feature engineering on large-scale security datasets.

Develop and optimize innovative security solutions for integration into Imperva products.

Collaborate closely with data scientists, security researchers, engineers, and product teams to deliver impactful solutions.

Actively participate in knowledge sharing, code reviews, and continuous team learning.

The Model Evaluation team is the central nervous system of the LTX Foundation Model group. We don't just measure performance; we define what "good" looks like across a vast array of use cases. While we power the next generation of creative tools, LTX is also a foundational engine for simulation pipelines, game engines, synthetic data generation, architectural rendering, and digital avatars. We act as the critical bridge between raw research and industrial-grade reliability, building the benchmarks that ensure our models are world-class for both artists and engineers.

The Role
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.

This role focuses on pioneering model architecture and pre-training algorithms, shaping the next generation of our foundational generative AI models.

What you will be doing
Pre-train and fine-tune video, audio, and image generative models to pursue state-of-the-art results.
Publish papers and open source models to benefit the research community and advance the field.
Design and implement machine learning models for text-to-audio and text-to-video generation.
Collaborate with data engineers to curate and preprocess text and video data.
Optimize models for high performance, ensuring efficient training and inference.
Build new controls and capabilities into generative text-to-audio and text-to-video models.
Stay updated with the latest developments in Generative AI, particularly in the fields of image, video, and audio.
Work closely with product teams to integrate AI models into applications and services.
Conduct experiments and prototype new concepts to advance the capabilities of our AI tools.