Senior Applied Scientist / Data Scientist (ML & LLM)

As part of the IT group, we are responsible for executing our enterprise data strategy which emphasizes data management maturity, fosters a robust data culture, and architects a best-in-class enterprise data platform. We have the ultimate goal to provide trusted data and insights at scale which enable corporate and functional data-driven decision making. We are fueled by organic innovation, internal collaboration and adoption of data visualization, data management, reporting automation, AI/ML and integration tools. We leverage best practices and alignment through our Enterprise Data Community to deliver speed to insight, scale, control and enablement. The team is distributed across the United States and India and is composed of data engineers, data analysts, visualization developers, and infrastructure specialists.

We are seeking an Applied Scientist / Data Scientist with deep expertise in machine learning, artificial intelligence, including the development and deployment of large language models. The ideal candidate will have a robust foundation in data science methodologies, with a particular focus on transforming Saas business models using the latest in AI technologies including both traditional and Generative AI methodologies. This role is pivotal to our mission of leveraging data to drive innovation, create efficiencies, and make informed business decisions. You will be reporting to Senior Manager, Data Science. You'll be responsible for:

• Design, develop, and implement machine learning models, including LLMs, to enhance the intelligence and functionality of Zscaler's internal and external tools.
• Conduct extensive research and development in cutting-edge areas such as generative AI, predictive analytics, anomaly detection, and other emerging technologies.
• Collaborate with engineering and product teams to integrate AI/ML technologies into Zscaler's solutions.
• Analyze large datasets to extract actionable insights and improve model accuracy and performance.
• Stay updated with the latest advancements in ML, AI, and cybersecurity to ensure Zscaler remains at the forefront of innovation.

What We're Looking for (Minimum Qualifications)

• Advanced degree (PhD preferred) in Computer Science, Machine Learning, Statistics, or a related field.- Track record of applied data science models (Regression, Decision Trees, K-Means, etc.).
• 5+ years of experience in NLP and the ability to process and analyze large amounts of natural language data.- Proficiency in programming languages such as Python, SQL, and experience with ML frameworks like TensorFlow and PyTorch.
• Strong understanding of ML algorithms, deep learning, neural networks, and their applications in cybersecurity.
• Knowledge in data manipulation, visualization, and analysis tools and techniques.
• Demonstrated ability to work on complex problems independently and as part of a team.
• Demonstrated skills in selecting the right statistical tools given a data analysis problem.

What Will Make You Stand Out (Preferred Qualifications)

• Strong background in mathematics, statistics, and the application of these disciplines in ML and AI with experience in both text generation and image generation large models.
• Experience with cloud computing platforms (AWS, Azure, GCP) and big data technologies (Hadoop, Spark).
• Familiarity with SQL, NoSQL databases, and data engineering principles for efficient data handling and manipulation.
• Expertise in deploying scalable machine learning models into production environments.

At Zscaler, we believe that diversity drives innovation, productivity, and success. We are looking for individuals from all backgrounds and identities to join our team and contribute to our mission to make doing business seamless and secure. For more information on our commitments to DEIB, visit the Corporate Responsibility page of our website.

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

• Multiple health plans
• A flexible time off policy
• Hybrid Working Model
• Parental leave options
• Retirement options
• Education reimbursement
• In-office perks, and more!

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