Job Description
At Zscaler, our AI and Data Science teams focus on various cybersecurity business-centric use cases including threat detection, policy recommendation, malware detection, content classification, anomaly detection, and AIOps (advanced networking diagnosis). As a Principal Data Scientist, you will have the opportunity to work on multiple fundamental machine learning problems addressing cloud security, cloud operations, and cloud intelligence.
You will be responsible for leading the development and implementation of advanced machine learning models, mentoring junior team members, and driving strategic AI and data science initiatives. You will have a deep understanding of various stages of an end-to-end Machine Learning project and will be capable of translating business problems into data-driven solutions.
Responsibilities
Lead the development of advanced machine learning models to address complex business problems
Mentor and guide team members on projects and professional growth
Collaborate with cross-functional teams to define project objectives and deliverables
Design, implement, and evaluate innovative machine learning solutions, ensuring alignment with business objectives
Drive strategic initiatives, identifying opportunities for improvement and innovation
Applied research: Stay up-to-date and apply the latest advancements in machine learning and data science
Communicate complex data science concepts to non-technical stakeholders and drive data-driven decision-making across the organization
Required Skills
2+ years of experience as a Machine Learning Engineer or Data Scientist, with a proven track record of leading and delivering successful projects
Expertise in Python (e.g., pandas, sklearn, pytorch) and SQL
Extensive experience in feature engineering, model evaluation, and error analysis
In-depth knowledge of Large Language Models (LLMs) and their applications
Master's or Ph.D. in Computer Science/Engineering or other technical field; data science concentration is a plus
Strong passion for leveraging ML/AI to solve real-world business problems at scale
Exceptional interpersonal, technical, and communication skills
Proven ability to learn, evaluate, and adopt new technologies quickly
Solid computer science foundation
Preferred Skills
Experience in prompt engineering and fine-tuning Large Language Models (LLMs)
Expertise in Graph Neural Networks/Knowledge Graphs
Proficiency in unsupervised learning (clustering) and evaluation
Research experience/publications/patents in relevant areas
Familiarity with public cloud services (such as AWS, Google, Azure) and ML automation platforms (such as Kubeflow)
Proficiency in various programming languages such as (Py)Spark
Deep understanding of operating systems and distributed systems
Knowledge of networking and networking security concepts
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