לוח משרות דרושים Data Scientist במרכז, לחיפוש זה נמצאו 62 משרות

We are seeking a talented and self-driven experienced Data Scientist to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact.

Responsibilities:

Develop and implement state-of-the-art econometric and machine learning models for demand forecasting.
Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability.
Collaborate with cross-functional teams (including product, data engineering, MLOPS and Platform) to deploy ML systems in production.
Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives.

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.

The Price Optimization (PO) team is where insights become decisions. We work with large-scale customer data and market predictions - like demand forecasts - to drive revenue management decisions that actually move the needle.

At our core, we build and maintain the decision-making engine. That means designing the data pipelines that bring customer data in, and running it through an optimization engine that simulates the market - weighing competition, pricing constraints, inventory availability, predictive models, and each client's unique business policies - to generate the best possible price recommendations. As the final step before recommendations reach the client, quality, reliability, and attention to detail aren't just nice to have. They're everything.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems-while growing and mentoring a high-performing team.

Responsibilities:

Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.
Design, build, and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data science engineering team.

seeking a data Scientist We are looking for a skilled data Scientist to join a model development team and lead the development of strategic, enterprise-wide AI and Machine Learning initiatives across business domains. This role requires strong hands-on experience in end-to-end model development, classic Machine Learning, classification and regression models, tabular data, data analysis, Python, and translating business requirements into technical and analytical solutions. A full-time hybrid position based in Central Israel, with 1 day a week remote. Key Responsibilities:
* Design, develop, and deploy Machine Learning models on AWS-based infrastructure.
* Derive actionable insights from data using advanced analytical tools and artificial intelligence technologies.
* Define algorithmic solutions to address complex business challenges.
* Analyze structured and unstructured data from diverse sources.
* Present analytical findings and strategic business insights to stakeholders.
* Evaluate and measure model performance and effectiveness.

We are looking for a passionate Data Scientist Team Lead to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment.

You will become the focal point of our data team and streamline processes, and will be responsible over company revenue streams.



What Youll Do

Mentor a team of extremely talented and success-hungry data scientists.
Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions.
Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs.
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems.
Identify and propose data science and algorithmic solutions for various product initiatives.
Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance.
Partner with other departments (i.e. Management, R&D, Product) to support decision making.

We are looking for a passionate Senior Data Scientist to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment. If you are experienced but still hungry to learn and impact - wed love to have you on our team!



What Youll Do

Devise, initiate, manage, and execute cutting-edge exploration and exploitation projects.
Apply your knowledge of Data Science, Machine Learning, and AI-driven algorithms to create scalable data solutions.
Analyze extremely large (petabytes) and diverse datasets to solve complex problems, and develop automated, intelligent systems to address them.
Design, build, and deploy AI/ML models (including predictive models, recommendation systems, and generative AI solutions) to drive business impact.
Leverage modern AI tools and frameworks to accelerate research and production workflows.
Proactively seek growth opportunities aligned with core KPIs.
Enable real-time and near real-time data insights - instant data gratification guaranteed.

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards

Were seeking a self-motivated Data Analyst with a strong sense of ownership and outstanding communication skills. As a key team member, you will play a crucial role in analyzing and deriving insights from product and marketing data to drive strategic decision-making. You will collaborate with various teams across the organization to optimize business processes, create and maintain BI reports and dashboards, and contribute to the companys data-driven culture.

You'll work directly with senior, data-driven stakeholders across the company, including executives outside Israel. Expectations are high, feedback is direct, and the work is visible. In return, you get real ownership, real impact, and the kind of proximity to business decisions that most analyst roles don't offer.


How Youll Spend Your Time
Surface actionable insights by identifying business trends, performance drivers, and anomalies across product, marketing, and financial data
Analyze large, complex datasets to answer strategic business questions and directly support decision-making across the organization
Define, track, and improve the KPIs that measure business and operational performance, ensuring stakeholders trust the numbers
Translate data into compelling visualizations and narratives that communicate key metrics, trends, and recommendations to business stakeholders
Drive product decisions through analytics and experimentation. Design and analyze A/B tests, measure feature adoption and funnel performance, and translate user behavior into insights that shape the roadmap
Build and maintain the data warehouse infrastructure, ETL pipelines, table structures, and schema design that powers reliable, timely analytics
Act as a subject-matter expert in analytics and BI tools, guiding stakeholders and team members toward better data-driven decisions
Own financial and transactional reconciliation. Validate revenue and performance metrics against partner-reported data at cent-level precision
Use AI tools effectively as a core part of the workflow, while maintaining a deep understanding of the data and code underneath

We are looking for a Senior Data Scientist to lead the development of machine learning solutions powering real-time decision-making and recommendation systems in industrial production environments.

This is a hands-on role with end-to-end ownership. You will be responsible for the full modeling lifecycle, from problem framing and data exploration to modeling, evaluation, deployment, and production impact. You will work with complex, noisy sensor and control data, building models that must be robust, interpretable, and reliable in real-world conditions.

You will collaborate closely with deep learning researchers, research engineers, and domain experts, and play a key role in shaping how data science is applied across the system.
Key Responsibilities


Design, develop, and evaluate machine learning models for real-time industrial applications
Own the end-to-end modeling pipeline, including problem formulation, data preparation, feature engineering, model development, evaluation, deployment, and post-production monitoring
Translate ambiguous production challenges into well-defined data science problems
Lead feature engineering and data exploration on complex sensor and control datasets
Define KPIs, evaluation frameworks, and experimentation strategies
Ensure model robustness over time, including monitoring, drift detection, and continuous improvement
Work closely with data and research engineers to bring models into production
Drive best practices in modeling, validation, and reproducibility
Communicate insights, trade-offs, and recommendations clearly to stakeholders

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

Design, implement, and train state-of-the-art neural network architectures for robotic applications, including large multimodal models (vision, language, sensor data) and generative models.
Architect and maintain scalable deep learning frameworks for training on massive, real-world robot datasets.
Develop and implement cutting-edge techniques in areas such as imitation learning, reinforcement learning, self-supervised learning, and video-based models.
Own the full machine learning lifecycle: define data collection and labeling strategies, build high-throughput data pipelines, and establish robust evaluation and deployment protocols.
Collaborate closely with software, hardware, and controls teams to integrate and test your models on physical robots.
Leverage and contribute to internal tooling for large-scale data processing, model experimentation, and continuous integration.

We are seeking an agile, hands-on R&D Lead who excels at rapid learning and making smart, pragmatic decisions to drive our core data engineering squad in Tel Aviv. We care less about years spent in formal management or having a decades-long resume, and much more about your ability to take extreme ownership, learn new paradigms on the fly, and keep the team moving forward.


In this role, you will help architect, write, and deploy the Python-based infrastructure that processes millions of records daily and serves them at sub-second latency to autonomous AI systems. You will guide the design of high-scale data pipelines, integrate semantic search paradigms, and build out our agentic connectivity layer. If you are a proactive decision-maker who thrives on optimizing complex systems and wants to build the infrastructure that LLMs rely on to understand the real world, this is your next role.


Key responsibilities
Execution & Decisive Leadership: Lead the technical delivery by setting the pace and making pragmatic architectural choices that keep the team moving forward. You prioritize shipping and iterating over analysis paralysis.
Hands-On Development (Python): Roll up your sleeves and remain technical. Write clean, concurrent, and scalable Python code to handle data ingestion, transformation, and serving pipelines.
Continuous Learning & Tech Agility: Work across a polyglot environment. You dont need to know every tool on day one, but you must be eager to rapidly evaluate, learn, and adopt the optimal databases, message brokers, and execution frameworks to manage technical debt.
Agentic Infrastructure & MCP: Deploy systems that allow autonomous agents to seamlessly query our datasets. You will help build and scale our Model Context Protocol (MCP) servers, translating LLM intents into highly optimized database queries.
High-Scale Data Pipelines: Oversee an end-to-end data architecture capable of supporting continuous ingestion, error cleansing, and near-real-time refreshing of a 1B+ record database while enforcing GDPR and CCPA compliance.
Search & Retrieval Integration: Design and optimize advanced search capabilities, leveraging vector databases, embeddings, and hybrid search techniques to ensure absolute precision when AI models query our data.

Are you a talented Data Scientist with expertise in image analysis and text reading? Are you passionate about leveraging cutting-edge technologies to drive innovation in the field of electronic component inspection? Look no further!

Responsibilities
Develop and implement advanced algorithms for image analysis and text reading in the context of component inspection.
Collaborate closely with cross-functional teams to enhance existing models and drive continuous improvement.
Work with large-scale datasets, applying statistical and machine learning techniques to extract meaningful insights.
Stay updated with the latest advancements in the field of image analysis and text reading and apply them to enhance our solutions.