דרושים » תוכנה » Data Scientist, Product Analytics

As a Data Scientist at our company, 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 wide-range 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 our company, 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 our company. 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
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

As a Data Scientist at our company, 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 wide-range 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 our company, you will become part of an 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 our company. 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.
This is a short term employment (STE) position.
Data Scientist, Product Analytics STE 18 Month Contract Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

We are seeking a Senior / Principal Security Researcher to join our innovative Security ML Team. Sitting at the forefront of endpoint protection, our team solves complex security challenges by applying advanced Deep Learning techniques, including resource-efficient Small Language Models (SLMs) and specialized ML algorithms to massive datasets, delivering groundbreaking security solutions directly into production.
In this role, you will serve as the core security domain expert within a multidisciplinary team of Researchers and Data Scientists. Working directly with complex malware behaviors, static file attributes, and massive telemetry, you will translate deep security insights into actionable datasets, automated rule-generation pipelines, and advanced feature sets.
Beyond classical security analysis, your research will directly drive, evaluate, and refine the AI models and detection logic that protect millions of endpoints worldwide, making this an ideal role for a security expert looking to apply data-driven methodologies and broaden their technical arsenal with AI/ML.
If you are a forward-thinking Security Researcher eager to autonomously drive high-impact research and shape the next generation of intelligent security modeling, we want to hear from you.
Key Responsibilities
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

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 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.

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.

As the Data Science Team Lead, you will lead a talented team of data scientists and ML engineers building the infrastructure, systems, and workflows for designing, training, evaluating, and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.

This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving, customer-specific model tuning, offline AI evaluations, and scalable ML systems in a production-grade SaaS environment.

If you are passionate about applied machine learning, fraud detection, and building intelligent systems at scale - we want you on our team.

What We Look for in Candidates:
Lead and mentor a team of Data Scientists focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.

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.

we are looking for a Data Scientist.
This is a high-impact, algorithm-focused Data Science role for a sharp ML practitioner who lives at the intersection of recommendation systems, user psychology, and feedback loops. As our Match Quality & Feedback Loops Expert, you will own the algorithmic core that powers meaningful connections on our platform. You are not here to just build models in isolation; you are here to continuous-tune evaluation metrics, solve cold-start and balance problems, and optimize real-time feedback loops that drive true user satisfaction, engagement, and long-term retention.
What You'll Do:
Algorithmic Match Quality: Design, train, and deploy production ML/AI models for recommendation engines, candidate ranking, and personalization to maximize match quality and user satisfaction.
Feedback Loop Optimization: Build and refine implicit and explicit feedback mechanisms (likes, messaging patterns, churn/retention signals) to continuously evolve algorithmic performance in real time.
Metric Frameworks & Evaluation: Define and implement robust online and offline evaluation frameworks, moving beyond naive accuracy metrics to measure long-term ecosystem health, fairness, and engagement.
Cold-Start & Liquidity Optimization: Develop innovative strategies to address cold-start problems for new users and balance marketplace liquidity across different geographic and demographic cohorts.
Cross-Functional Collaboration: Work hand-in-hand with Product Managers, Data Engineers, and Core AI/ML teams to translate complex behavioral insights into actionable product features.

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.