לוח משרות דרושים Data Scientist משרה מלאה, לחיפוש זה נמצאו 66 משרות

As a Staff Data Scientist your role will be to:

Use analytical, statistical and technical skills to understand large, complex datasets with the aim to eliminate waste and measure incrementality for advertisers.
Lead, Develop & improve algorithms for automated decision making around lifetime value, causality, multi-touch attribution, and media mix optimization
Determine, analyze, maintain, and report on core marketing metrics to identify causal relationships between marketing actions and outcomes.
Translate data into actions and recommendations - appropriately interpreting and building on findings, and fully exploiting insights

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.

This is a full-time, on-site role for a Data Engineer Ltd., located in Haifa. The Data Engineer will design, build, and maintain scalable data pipelines, implement robust Extract, Transform, Load (ETL) processes, and develop efficient data models to support business intelligence and data analytics needs. The role also involves building and improving data warehousing solutions and collaborating with cross-functional teams to ensure data integrity and optimize workflows.

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
Responsibilities
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows.|Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security.
Collaborate with engineering teams to design, build, and maintain production pipelines.
Work closely with the Security Research and Product teams to define research goals.
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

We're looking for a Senior Data Scientist who loves what they do: a strong foundation in machine learning, statistics, and software engineering, a passion for modern AI-accelerated development, and the drive to own research, design, and end-to-end delivery of ML systems that ship to millions.

What you'll be doing


Research, train, and deploy state-of-the-art recommender systems using deep learning and GenAI
Own projects end-to-end - from business idea through modeling, experimentation, and production deployment - including the parts that involve aligning other people around them
Build online, scalable models and serving solutions that leverage massive datasets and reach hundreds of millions of users
Apply multimodal and sequence-modeling techniques to real product problems where model improvements translate directly to business impact
Lead cross-team initiatives, improve the tooling the team works with every day, and mentor others as you go
Collaborate with ML experts, big data engineers, product managers, and developers across the organization to solve complex problems

We are hiring an Applied Data Scientist to build the models that turn raw transaction data into the insights our banks customers see every day.
The stack is deliberately wide: classical ML on tabular data, deep learning, LLM-based systems, and agentic flows. We choose the right approach for each problem, balancing analytical quality, production readiness, and time to market. You drive the analytical work, working closely with Product and Engineering to take ideas from evidence through production.
Responsibilities:
Analyze and interpret complex datasets to identify trends and patterns.
Collaborate with cross-functional teams to develop data-driven solutions.
Build and maintain predictive models to enhance business decisions.
Communicate findings and insights effectively to stakeholders.
Stay updated with the latest data science technologies and methodologies.
Contribute to the continuous improvement of data processes and systems.

As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.

In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.

What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.

Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.

Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.

Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.

Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.

Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.

Required Research Data Scientist II, Waze
About the job
The Personalized Experience team aims to give Waze drivers personalized, hyper-local, contextual and timely routing experience. The team contributes to the Personalized Navigation squad and more. The team members are embedded within the Waze development Squads. We develop and own Machine-Learning models from ideation to production, including research, production grade pipelines, feature engineering, experimentation, monitoring and dashboards, inspection and debugging.
The team works closely with the product team, helping to shape the requirements and success metrics. The team works closely with the Backend teams, integrating the models, ensuring a feedback loop to enrich the models, triage and solve users complaints, leading and guiding experimentation and more.
Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.
Responsibilities
Feature engineering, model evaluation and error analysis, data processing and pipelines, model tuning, monitoring and dashboards.
Work with product managers, software developers and quality analysts to define requirements, formulate success metrics and lead experimentation.
Use data to help products to shape the future of Waze and drive innovation. Provide insights on user behavior and help engineers and quality analysts detect and solve complex problems.
Utilize Cloud Platform, Vertex AI, Python, Scikit-learn, TensorFlow, Airflow/Composer, Python and Looker tools.

we are looking for an experienced Data Scientist to join us and take a key role in turning large-scale, real-world data into smarter product and business decisions.With millions of users interacting with mobility services, our data reflects complex customer behavior, business models, and real-life mobility patterns.We're looking for someone who can go beyond building models - someone who knows how to identify the right problems, challenge assumptions, uncover opportunities in the data, and translate them into real business impact.
You'll have significant professional ownership, from taking an ambiguous business question and framing it as a statistical or Machine Learning problem, through choosing the right methodology, building and evaluating the solution, and bringing it to production.Just as importantly, we expect you to proactively identify questions that should be answered with data - even when nobody has asked them yet.
Responsibilities:
Own Data Science problems end-to-end - from business question and hypothesis to modeling, evaluation, and production.
Partner closely with Product, Business, Data, and Engineering teams to translate complex business challenges into data-driven solutions.
Proactively identify opportunities where statistical analysis, Machine Learning, and AI can improve our products, customer experience, and business performance.
Build, train, evaluate, and improve Machine Learning models used in production, across both real-time and batch use cases.
Select the right statistical or ML approach based on the problem and the data - including recognizing when a simple analytical solution is better than a complex model.
Define meaningful evaluation methodologies and connect model performance to real business impact.
Communicate complex statistical findings clearly to both technical and non-technical stakeholders.

We are looking for a Senior Data Engineer with strong Python expertise and extensive experience building large-scale, distributed data systems.

You will play a key role in developing our next-generation data platform, building integrations with external data sources, and designing the services and pipelines that collect, process, and serve large volumes of data across our product.

You will own systems throughout their full lifecycle - from system design and hands-on development to deployment, scalability, and production monitoring - while contributing to technical decisions and working closely with the team on building reliable, high-performance data solutions.

Our Office is located in Kiryat Ono.This is a hybrid position, including two work-from-home days per week, with flexibility .

This role combines deep technical expertise with leadership responsibility, driving multidisciplinary Data Science initiatives end-to-end within complex security policy management systems.

The role drives the development of innovative, production-grade AI capabilities, including the intelligence behind security AI agents and advanced machine learning models built on complex security data.

Original thinking, deep technical rigor, intellectual agility, and exceptional problem-solving are essential.

Responsibilities:

Lead end-to-end Data Science initiatives from problem framing through validation, CI/CD-based production deployment, monitoring, and ongoing operational optimization of AI systems

Develop advanced ML capabilities, including predictive modeling, anomaly detection, classification, and behavioral analysis

Develop the intelligent capabilities behind security AI agents, combining machine learning, LLMs, statistical methods, and domain-specific algorithms, with a strong understanding of how agents use these capabilities within multi-step workflows

Adapt and fine-tune LLM technologies for domain-specific security use cases

Define and implement rigorous evaluation methodologies for ML and agentic AI systems, including decision quality, reliability, robustness, uncertainty, and failure modes

Partner with Product, Engineering, and Security teams to deliver measurable business impact

Provide technical leadership and mentorship across multidisciplinary Data Science initiatives

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.

Were looking for a Data Scientist to join our R&D department!
Why is this role so important?
A data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help 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 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 out-of-the box requests from customers who want custom digital insights.
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.