לוח משרות דרושים Data Scientist במרכז, לחיפוש זה נמצאו 45 משרות

abra R&D is looking for a Senior Data Scientist for AI Agents Platform: abra R&D is building a next?generation database platform for AI Agents and is looking for a Senior Data Scientist to join the core product team. This role is research?oriented and focuses on developing analytical methodologies, statistical models, and algorithmic foundations for an agentic analytics platform operating on large?scale, real?time data. The position sits at the intersection of applied research and product, with a strong emphasis on experimentation, inference, and translating theoretical approaches into practical decision?making systems. Responsibilities: Analyze large?scale structured and unstructured data to extract actionable insights
* Design and develop statistical and machine?learning algorithms for analytics and decision systems
* Build and evaluate models for forecasting, anomaly detection, and decision support
* Apply causal inference methods to measure impact and understand relationships in data
* Design and analyze experiments (A/B tests, uplift modeling)
* Define statistical methodologies used across the platform
* Collaborate with AI and engineering teams to translate models into product features
* Communicate insights clearly to technical and non?technical stakeholders

Required Customer-Facing Data Scientist - Demand Forecasting
Demand Forecasting Team
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

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.

Were looking for a data scientist to join our team and further improve fraud detection capabilities.
This position involves analyzing evolving fraud patterns, developing and deploying advanced prevention components, and leveraging domain expertise, data tools, and modern AI methods to stay ahead of emerging threats.
A partial list of our tech stack: Python (and its related scientific stack), Spark, TensorFlow/PyTorch, Kafka, AWS services, Airflow, Scala, BigQuery, and more
What you'll do:
Mine massive data sets to uncover fraud patterns and prevention opportunities.
Develop and productionize large-scale ML, DL, and AI models to detect and prevent fraudulent activity.
Translate business and product needs into scientific, explainable, and high-impact solutions.
Design and maintain end-to-end ML pipelines - from data ingestion and feature engineering to serving and monitoring in production.
Collaborate closely with product, engineering, and business teams to drive data-driven decisions.
Stay current with AI and ML research and evaluate new technologies to strengthen Protect360s algorithms.

We are looking for a Senior Product Manager to join our Analytics team within the Measurement group. In this role, you will own a core analytics domain used daily by global advertisers to measure, interpret, and optimize their marketing performance. You will work at the intersection of large-scale data, attribution complexity, privacy-driven measurement changes, and AI-powered capabilities - shaping how customers understand and rely on their marketing data.
This is a high-impact, highly visible role with direct influence on customer trust, product strategy, and the evolution of AppsFlyers analytics platform.
What youll do:
Own a core Analytics domain end-to-end - from discovery and strategy definition to execution, launch, and continuous improvement.
Define and drive the roadmap for dashboards, metrics, and data experiences serving enterprise marketing teams.
Balance stability, scalability, and innovation in a complex, data-intensive environment.
Lead initiatives that modernize and consolidate analytics capabilities across multiple attribution sources.
Shape the integration of AI-powered capabilities into analytics experiences, enhancing how customers interpret performance data.
Work closely with R&D (Backend, Frontend, Data Engineering) to build scalable, high-performance analytics products.
Partner with Sales and Customer Success to understand customer needs, support adoption, and strengthen trust in our measurement solutions.
Engage directly with customers to validate product direction and identify opportunities to improve clarity, usability, and performance insights.
Drive prioritization in a high-demand environment with multiple stakeholders and competing initiatives.

Are you a Masters or PhD student interested in a 2026 Internship in Data Science? If so, we want to hear from you!

We are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment and is comfortable owning data to drive step-change innovation in the EMEA region or worldwide.

As a Data Science Intern, you will have the following key job responsibilities:
Work closely with scientists and engineers to develop new algorithms to implement scientific solutions for our problems.
Design, run, and analyze A/B tests.
Work on an interdisciplinary team on customer-obsessed research.
Experience our customer-focused culture.
Create and deliver projects that can be quickly applied starting locally and scaled to EMEA/worldwide.
Create and share data with audiences of varying levels technical papers and presentations.
Define metrics and design algorithms to estimate customer satisfaction and engagement.

Key job responsibilities
- Experimentation at scale: Design, execute, and analyze A/B tests, from short-cycle learning experiments to full product launches across worldwide marketplaces.
- Measurement & metrics: Build frameworks to measure content discovery quality, search recall, recommendation relevance, and broadcast experience, including novel methodologies for live, time-sensitive content.
- Sports analytics: Deep-dive into customer behavior around live events: engagement patterns, affinity segmentation, broadcast quality, and tentpole event dynamics.
- Product partnership: Partner with Applied Scientists, Engineers, and Product Managers to define requirements, evaluate models, and drive data-informed decisions.
- Analytical leadership: Own data structures, metrics definitions, and best practices. Communicate findings clearly to technical and business stakeholders.
- Shape a growing domain: Help define the data science roadmap as we expand into new areas of live sports.

We are looking for a hands-on security researcher who combines an attacker mindset, fraud-domain curiosity, strong technical depth, and data analysis skills. You will investigate real-world fraud patterns, reproduce attacker techniques, analyze telemetry, enrich our data collection capabilities, discover new security signals, and work closely with product, data, and engineering teams to turn research insights into production-grade detection and prevention mechanisms.
This role is especially relevant for researchers with experience in browser technologies, mobile-native applications, or both. You may work on desktop and mobile browsers, browser APIs, browser automation, client-side signals, native mobile applications, Android/iOS behavior, mobile security, emulators, device signals, and mobile automation.
You will help expand our visibility into new signals and patterns that improve fraud detection, model performance, and customer protection.
If you are a talented researcher who enjoys solving complex problems, working with messy real-world data, and building practical defenses against modern fraud and abuse, we want you to join our team.

We are looking for a Senior AI Researcher to work closely with our delivery team, translating real-world clinical and scientific questions into rigorous AI and machine learning solutions. In this role, you will lead the development of methodologies, models, and benchmarking frameworks that address complex clinical problems using our unique immune-cell data. Your work will directly impact how our partners understand biology, evaluate hypotheses, and make decisions.

Location: Ramat Gan (hybrid model).

What will you do?
Partner with the collaborations team and scientists to frame complex clinical and biological questions as well-defined data science and modeling problems.
Design, implement, and evaluate the right analytical and modeling approaches for each problem, including robust benchmarking and validation strategies.
Clearly communicate results, limitations, and tradeoffs to internal teams and external partners, enabling confident, data-driven decisions.
Establish best practices for rigor, reproducibility, evaluation, and documentation across delivery-focused data science work.
Work hand-in-hand with immunologists, computational biologists, AI scientists, and engineers to ensure solutions are scientifically sound and production-aware.
Translate modeling solutions into engineered and iterable products used by the internal collaborations team.

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

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.

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.

Do you want to take part in shaping the future of AI-driven materials discovery? We are seeking a talented and highly motivated student for a Joint PhD at Bar-Ilan University (BIU), to conduct cutting-edge research in collaboration with our teams, on next-generation Foundation Models for Materials Science.
The work will focus on developing novel multi-modal foundation models for materials discovery, leveraging large-scale data, representation learning, and uncertainty estimation. The candidate will work closely with academic and industry researchers, contributing to both methodological advances and real-world impact across scientific and industrial domains.
What youll be doing:
Conduct research in deep learning and AI for materials science, with a focus on foundation models, multi-modal learning, and representation learning.
Develop and train large-scale models for materials discovery and prediction tasks.
Collaborate with researchers and engineers across and academia.
Lead independent research under academic supervision, while contributing to team efforts.
Publish results in top-tier conferences and journals, and present findings clearly and effectively.