לוח משרות דרושים Data Science Team Leader

As a Data Science Team Leader , you will lead a high-performing team developing AI/ML solutions that secure the digital worlds most sensitive assets. Youll play a key role in driving innovation, productizing machine learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges. In this leadership role, youll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. Youll work closely with data scientists, engineers, analysts, product managers, and Cyber-Security researchers to build intelligent features across identity security portfolio.

Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
Champion best practices in MLOps, data governance, explainability, and monitoring.
Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

Required Data Scientist Team Manager
A day-to-day role as a Team Manager includes:
Managing a multidisciplinary team of data engineers, data scientists, and data analysts.
Leading the development of advanced and creative solutions for complex technical challenges in areas like big data and machine learning.
Collaborating closely with data extraction, platform, and product teams.
Communicating with business stakeholders and gathering feedback from customers.
Hiring new team members and developing the groups structure.
Playing a crucial role in shaping product strategy within a startup-like environment.
Day-to-day, the team you will lead will:
Develop statistical and machine learning algorithms on large-scale data to estimate metrics, create features, and deliver insights.
Own end-to-end data processes and pipelines, from research and proof of concept to production.
Collaborate with product and R&D teams to plan and deliver best-in-class digital insights.
Design, validate, and monitor ongoing processes to ensure quality and reliability.
Identify, analyze, and monitor new raw data sources as needed.

We are looking for a Applied AI Team Lead.
As the Team Lead for our Applied AI team, you will join our Tel Aviv office. You will guide the day‑to‑day execution of innovative projects to help mayors and other city leaders understand their communities and improve the lives of millions worldwide. Reporting to the VP of Data Science, you will combine hands‑on technical leadership with people management skills, overseeing a team with rapidly-growing portfolio of mission-critical projects and collaborating with product, engineering, and other internal partners. Youll be responsible for leading every aspect of the development process, so that our cutting‑edge AI and data science capabilities get to production quickly, reliably, and with maximum impact.
Day to Day:
Lead a 5‑person team of data scientists and engineers, coordinating stand‑ups, code reviews, and 1‑on‑1s while also contributing hands-on to high-priority projects.
Oversee the development and implementation of a diverse project portfolio, focused on both customer-facing product features and internal business use cases.
Scope, execute, and deliver end‑to‑end AI and data science capabilities to meet the requirements of product owners and internal stakeholders.
Play a leading role in the development of AI-focused infrastructure and the implementation of best practices for engineering and data science.
Track project risks, dependencies, and costs, and make proactive adjustments to keep initiatives on time and aligned with requirements.
Stay current with the latest developments in AI technologies and tools, and identify opportunities to integrate the latest innovations into our products and workflows.
Recruit, onboard, and develop team members to help scale our Applied AI program and promote a culture of technical excellence.
Work an in‑person or hybrid schedule, with at least three days per week in our Tel Aviv office.

Were looking for a Data Science Team Lead to join our winning team. This is an opportunity to take a leadership role in building innovative AI products, manage a growing team of algorithm researchers, and have a major impact on the methods, infrastructure, and product capabilities.

Youll lead projects from early research to full production deployment, guiding the development of models, scalable pipelines, and services that power critical features in the platform.

Responsibilities:
Lead, mentor, and grow a team of Data Scientists providing both technical leadership and professional development.
Own the full lifecycle of AI projects: from research and prototyping through production-grade deployment and monitoring.
Design and oversee the development of scalable ML pipelines, model serving infrastructure, and robust data workflows in collaboration with software engineering and product teams.
Drive initiatives to deliver LLMs and other AI models as production-grade services within the organization.
Partner cross-functionally with product managers, clinical experts, and engineers to translate business needs into AI-driven features.
Guide research in NLP, NLU, and Deep Learning domains, staying at the forefront of industry developments and incorporating new methods where applicable.
Maintain a high standard of technical execution within the team, fostering a culture of ownership, quality, and innovation.
Communicate technical findings, project status, and strategic recommendations clearly to technical and non-technical stakeholders.

As the Data Scientist Team Lead, you will oversee and guide our data science team, driving the development and deployment of advanced machine learning models, with a particular emphasis on Natural Language Processing (NLP). Your responsibilities will include managing and optimizing our Natural Language Understanding (NLU) models, leading prompt engineering efforts for Large Language Models (LLMs), and conducting thorough NLP assessments. You will also ensure the continuous monitoring and refinement of these models to maintain peak performance. These models will be seamlessly integrated into our core products, playing a critical role in advancing our strategic objectives.

What Youll Do:
Manage Data Science Team:
Responsibility of Fullstack DS from development to production.
Performing multiple assignments for Natural Language Processing (NLP).
Responsibilities over Natural Language Understanding (NLU) models.
Developing and implementing machine learning models in a production environment.
Handling prompt engineering tasks.
Monitoring and optimizing models.

We are looking for a Data Scientist Team Lead.
Responsibilities
As an AI/ML Team Lead, your responsibilities include:
Leading and mentoring a team of AI engineers, fostering a culture of innovation, collaboration, and continuous learning.
Working with product managers, software engineers, and designers to identify and prioritize AI-driven features and enhancements.
Developing the next generation of DPI and QoE AI/ML engines and integrating them into the product.
Maintaining existing AI/ML engines.
Promoting best practices in AI development, including model evaluation, testing, and monitoring.

Required Data Science Team Lead
Description
Connecting people across the world is a complex problem with many machine-learning applications. The purpose of this role is to implement mathematical models and algorithms to solve complex business problems. Successful outcomes will significantly impact our hundreds of millions of daily active users around the globe.
As a Data Science Team Lead your leadership and expertise will progress our AI vision and strategy. This role demands a strong background in mathematics and statistics. You will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems at a high standard.
Responsibilities
Be a technical leader of data scientists, with substantial scope, impact, and visibility. Mentoring and providing guidance and support to foster their growth and success.
Work with management and partner teams to design and implement key results for the companys most strategic initiatives.
Own the full data science lifecycle, including problem definition, data collection, model development, evaluation, deployment, and monitoring.
Autonomously find solutions to complex data science problems, with potentially non-trivial solutions, and understand the data generation process and challenges with the data.

We are seeking an experienced Data Science Lead to join us and play a key role in shaping the future of data security. As a Data Science Lead, you will be part of our Classification team, which lies at the core of our missionidentifying sensitive data and helping customers detect the most critical risks in their cloud environments. Our multidisciplinary team of data scientists, analysts, and engineers collaborates to build the worlds most effective sensitive data detection system.
Responsibilities
Lead the design, development, and deployment of machine learning models, including NER and LLMs, to enhance our data classification and entity recognition capabilities.
Collaborate closely with Product and Engineering to align cutting-edge AI technologies with real-world customer needs and our roadmap.
Build and maintain a robust experimentation framework to accelerate model iteration, evaluation, and deployment.
Leverage our extensive datasets to define key quality metrics and drive continuous improvements in classification accuracy.
Adapt quickly to evolving customer needs while maintaining high standards of model performance and reliability.
Innovate by identifying new opportunities to improve accuracy, automate workflows, and introduce AI-driven features that provide value to our customers.