דרושים » דאטה » Senior Staff Data Scientist (AI Solutions - Machines)

As a Data Scientist at CyberArk, youll join a team shaping the future of identity security and pioneering research in areas of cybersecurity and Agentic AI.
Advance your data science career by applying your established expertise to solve complex, real-world problems at scale and drive innovation alongside leaders in the cybersecurity and AI space.
Research, design, Evaluate and production deployment of advanced AI/ML models, specializing in LLMs, RAG systems, and Agentic AI applications.
Explore and analyze large-scale datasets to uncover patterns and drive actionable insights.
Collaborate closely with product managers, engineers, and analysts to support feature development and validate ML ideas.
Stay up to date with the latest academic and industry trends in AI/ML and apply best practices to real-world challenges.
Grow your skills in classic machine learning, deep learning, natural language processing (NLP), LLMs and cybersecurity applications.

As a Data Science Manager, you will lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions. You will own the end-to-end development lifecycle of AI projects, from exploratory research and experimentation through to scalable deployment and optimization. In this role, you will partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery. You will also drive innovation across a broad spectrum of ML domains, including supervised/unsupervised learning, anomaly detection, and generative AI, while providing hands-on guidance and championing best practices in MLOps, data governance, and model evaluation.
Key Responsibilities
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.

We're looking for a Data Scientist to turn our network data into a competitive advantage. You'll work directly with terabytes of telecom signaling, session, and usage data to build models that improve network selection, detect anomalies, optimize cost-per-gigabyte, and surface insights that shape product and commercial strategy. This is a high-impact role sitting at the intersection of ML, telecom engineering, and business decision-making.

What You'll Do

Design and deploy machine learning models on network data - including network selection optimization, churn and usage prediction, fraud and anomaly detection, and QoS/QoE forecasting.

Analyze CDRs, signaling events (Diameter, GTP, SIP), session logs, and radio-level metrics to identify performance issues, cost drivers, and growth opportunities.

Partner with the Network Operations and Product teams to translate raw telemetry into actionable signals - e.g., which carrier to steer traffic to in a given country at a given hour.

Build forecasting and segmentation models that inform pricing, capacity planning, and customer lifecycle strategy.

Own analyses end-to-end: framing the business question, exploring the data, building the model, validating it, and communicating findings to both technical and executive audiences.

Define and track KPIs for network quality, customer experience, and commercial performance, and build dashboards that make those metrics visible across the company.

Mentor junior data scientists and analysts, and help raise the bar on data science practices, code quality, and experimentation rigor.

A True Problem Solver Were looking for a Senior DS who thrives on End-to-End ownership. You aren't just given a dataset; you identify the business opportunity, architect the mathematical solution, and write the high-quality, production-ready code that brings it to life. This is the ultimate "DS Candy Store" for those who love research but live for the adrenaline of seeing their code drive real revenue.
What Youll Do:
End-to-End Ownership: Own the entire lifecycle: from defining the business problem and KPI to deploying and monitoring the solution in production
High-Scale Architecture: Design and implement ML models & handling high-cardinality data at massive scale
Engineering Excellence: Write clean, modular, and scalable code. We believe great Data Science is built on a foundation of great Software Engineering
Strategic Leadership: Mentor the team through complex technical hurdles and contribute directly to our algorithmic roadmap