לוח משרות דרושים Data Scientist בתל אביב יפו, לחיפוש זה נמצאו 53 משרות

we are looking for a Research Scientist - Sovereign AI Research.
We are hiring across the following specializations. We expect depth in at least one area and the intellectual range to collaborate across them.
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Define and execute a research within your track, experiments, quality gates, and upper bounds in rigorous manner.
Collaborate across tracks on system integration and cross-disciplinary research.
Collaborate work with engineering teams until production.
Mentor junior researchers and contribute to a culture of technical excellence

we are looking for a AI Applied Scientist - Insights & Recommendations.
As AI Applied Scientist, youll be at the intersection of advanced technology and meaningful impact with clear business cases. You will have access to real-time (RT) big data from multiple Sensors & Data sources, and a chance to discover, explore research, and develop cutting-edge models that directly impact industrial manufacturers around the globe. As part of the Applied AI/ML Science team , you will have the opportunity to continuously grow and learn while building and deploying advanced models directly into our products, and stay at the forefront of the world's technologies, witnessing firsthand their impact on our customers.
A Day In Your Life:
Own the algorithm lifecycle from problem definition and data analysis to prototyping and delivering production-ready models.
Combine classic methods with inference techniques: statistics, Time series, Deep learning, anomaly detection, Recommendation Systems, Transformers, and Inference to extract data-driven insights.
Research, design, and build Agentic applications on top of sensor time-series data, textual data, images, ML applications, and other various data sources.
Engage with customers and collaborate with our product team to develop innovative solutions utilizing new types of data.
Leverage modern technologies: work with cloud-based big data platforms for storage, distributed processing, LLMs and agents (GPT, Claude, Gemini), defining & building Gurdrails, reasoning chain as function call, planning, ML-based vectorization and embeddings, and stream analysis.

As a Data Scientist you will be working with colleagues from various disciplines - Research Engineers, Analysts, and other Data Scientists - on statistical methods and machine learning techniques and Gen-AI (both supervised and unsupervised) in order to develop classification and anomaly detection algorithms.

We are seeking a talented and motivated Data Scientist for a temporary position to support our growing data, analytics, and AI automation needs. This role focuses on turning large volumes of data into models, insights, and intelligent automation - combining classic data science (statistical analysis, feature engineering, machine learning) with the emerging Agentic AI stack (LLMs, MCP, agent orchestration). You will work closely with data engineers and internal teams to prototype and productionise models, build LLM-powered agents and workflows, and support the integration of AI capabilities across the organization.

The ideal candidate is passionate about data and AI, comfortable navigating complex systems, and excited by the opportunity to operationalize AI within a modern enterprise environment. We value curiosity as much as experience: we are looking for someone eager to show what they know, and equally eager to keep learning in a field that moves fast.


Responsibilities
Explore, analyze, and model large volumes of structured and unstructured data in Python, from exploratory analysis and feature engineering through to model validation and communication of results.
Design, train, evaluate, and deploy machine learning models, and monitor their performance, accuracy, and drift in production.
Build and orchestrate Agentic AI solutions - LLM-based agents, RAG pipelines, prompt design, and evaluation frameworks - to automate data quality checks, investigation, and reporting workflows.
Integrate models and agents with internal systems and data sources using MCP servers and clients, and workflow automation platforms such as n8n.
Write efficient and maintainable SQL queries to support analysis, reporting, and data exploration needs.
Collaborate with data engineers to productionise models and agents: reliable data flows, logging, alerting, and performance tuning.
Participate in the development of internal tools and dashboards that make data and AI capabilities accessible across the organization.
Share findings with the team and help evaluate emerging AI tooling as the ecosystem evolves.

We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth.

Key job responsibilities
- Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, build, and operate innovative products and services that delight our customers, while participating in technical discussions to drive solutions forward.
- Design and develop scalable solutions using cloud-native architectures and microservices in a large distributed computing environment.
- Participate in code reviews and contribute to technical documentation.
- Build and maintain resilient distributed systems that are scalable, fault-tolerant, and cost-effective.
- Leverage and contribute to the development of GenAI and AI-powered tools to enhance development productivity while staying current with emerging technologies.
- Write clean, maintainable code following best practices and design patterns.
- Work in an agile environment practicing CI/CD principles while participating in operational responsibilities including on-call duties.
- Demonstrate operational excellence through monitoring, troubleshooting, and resolving production issues.

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 varied set 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 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
Defining new opportunities for product impact Influencing product and sales to solve the most impactful market problems
Apply your expertise in quantitative analysis and the presentation of data to go beyond the numbers and understand how our users interact with our growth products
Work as a key member of the product team to solve problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches in partnership with Product, Engineering, and cross-functional teams
Set KPIs and goals, design and evaluate experiments, monitor key product metrics, understand root causes of changes in metrics
Exploratory analysis to discover new opportunities: understanding ecosystems, user behaviors, and long-term trends Identifying levers to help move key metrics.

Were looking for a sharp and driven Product Data Scientist to join our fast - paced Data Labs team. As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights. The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure. Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.

What does the day to day of a Product Data Science Customer Facing (Data Labs) look like:

Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools which will help answer client's business. questions by using raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly

Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.

As part of this role, you will create and support a complex data model pipeline that helps 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 engineer in the Datalabs team, you will work on the very core of the company. Part of your role will be to create processes that help turn raw data into usable metrics and leverage AI models and statistical algorithms to support out-of-the-box requests from customers who want custom data labs. The Datalabs departments business-oriented nature also means you will be supporting a team of analysts and data scientists who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class data labs.

So, what will you be doing all day?

Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark

Were looking for a sharp and driven Data Analyst to join our fast - paced Data Labs team. As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights. The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure. Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.

What does the day to day of a Big Data Analyst Customer Facing (Data Labs) look like:

Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools which will help answer client's business. questions by using raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly

Were looking for a Data Scientist to join our R&D department!


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

1. AI Architecture & Technical Leadership

Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.

2. Hands-on Applied Innovation (Core Pillar | ~50%)

Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:

De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering

3. Best Practices & Technical Enablement

Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)

Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

we are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of primary products. This involves working on core systems, such as POS underwriting models, models for merchant operations, Fraud investigator AI agents and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / fraud / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g. providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Analyze 15+ different data sources in order to train models and agents to catch fraudulent patterns.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

We are rapidly growing into new verticals, and we are seeking a visionary Developer Relations Senior Manager to broaden our impact. In this regional leadership role, you will champion Israels growing AI ecosystem, managing a high-performing team of Developer Relations Managers.

You will lead technical projects in GenAI/ML application development, consumer internet, and embedded AI systems. Working at the crossroad of engineering, strategy, and community, you will promote our hardware and SDK offerings. This role supports faster adoption of GPU-accelerated technologies by developers, startups, and ISVs. If you are a technically fierce, highly autonomous leader who thrives in a matrixed environment and wants to build the future of AI, let's talk.

What Youll Be Doing:

Lead & Mentor: Guide, collaborate and encourage a regional team of Developer Relations Managers covering Israel's dynamic AI ecosystem.

Drive Technical Strategy: Architect and complete a comprehensive developer adoption strategy for key industries, ensuring our platforms remain the gold standard.

Build Technical Alliances: Establish deep, positive relationships with CTOs, engineering leads, startups, and ISVs within the local ecosystem.

Evangelize & Accelerate: Act as the ultimate technical mentor and focal point for the developer community. Help developers unlock the full value of our SDKs and hardware to solve complex, real-world problems.

Champion the Community: Lead our presence at targeted developer events, hackathons, and industry activities.

Bridge the Matrix: Collaborate across internal product divisions, sales geographies, solution architects, and marketing teams to align our local ecosystem strategy with global value messaging.

We are seeking a Senior NLP/LLM Researcher to conduct advanced research and develop innovative applications focused on protecting and evaluating LLMs & agentic applications. In this role, you will collaborate with a multidisciplinary team of scientists and engineers, working together to address critical challenges. You will be responsible for designing, implementing, and evaluating new algorithms, models, and agents that help safeguard LLMs.

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‍Key Responsibilities:

Create real-time protections: Develop innovative methods to detect and mitigate adversarial attacks on agents and keep them in line with the organization's policy such as avoiding hallucinations, leaking personal data etc.
Develop new and unique evaluation methods: Implement and develop advanced metrics to evaluate agents' performance on multiple fronts.
Research and Development: Conduct research on adversarial attacks, model protections and performance evaluation techniques for NLP models. Explore and develop state-of-the-art methods and propose innovative solutions.
Collaboration: Work closely with other team members, participate in brainstorming sessions, and contribute to the team's success.