Staff Data Scientist

| Remote | Hybrid
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Company Description
Zscaler (NASDAQ: ZS) accelerates digital transformation so that customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange is the company's cloud-native platform that protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
With more than 10 years of experience developing, operating, and scaling the cloud, Zscaler serves thousands of enterprise customers around the world, including 450 of the Forbes Global 2000 organizations. In addition to protecting customers from damaging threats, such as ransomware and data exfiltration, it helps them slash costs, reduce complexity, and improve the user experience by eliminating stacks of latency-creating gateway appliances.
Zscaler was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. Zscaler's purpose-built security platform puts a company's defenses and controls where the connections occur-the internet-so that every connection is fast and secure, no matter how or where users connect or where their applications and workloads reside.
Job Description
As a Staff Data Scientist, you will work in an award-winning team that does full-lifecycle full-stack Machine Learning product development , from feature engineering to model building and evaluation.
Our team's use cases include but are not limited to threat detection, malware detection, content classification, anomaly detection, and AIOps (advanced networking diagnosis). These various use cases give you the opportunity and challenges to experience multiple machine learning algorithms and tools. You will design and create machine learning models to provide faster and more effective ways to address cloud security, cloud operations, and cloud intelligence use cases.
You might not be an expert in every stage of a Machine Learning project, but you should have interests and curiosity in various parts ranging from the data to the model's business impact.
Qualifications

  • Passion for leveraging ML/AI to solve real-world business problems (better security and better business results).
  • 5+ years of industry experience in one or more machine/deep learning frameworks.
  • 5+ years of industry experience with Python and SQL
  • Bachelor or Master's Degree in Computer Science required, data science concentration is a plus; PhD is preferred
  • Excellent interpersonal, technical, and communication skills.
  • Good business sense.
  • Ability to learn, evaluate, and adopt new technologies fast
  • Ability to lead and execute projects from start to finish.
  • Solid computer science foundation


Desirable Skill Sets:

  • Experience with various public cloud services (such as AWS, Google, Azure) and ML automation platforms (such as Kubeflow).
  • Experience with various program languages such as Go.
  • Good understanding of operating systems and distributed systems.
  • Familiarity with networking and networking security.


Additional Information
All your information will be kept confidential according to EEO guidelines.
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What You Can Expect From Us:

  • An environment where you will be working on cutting edge technologies and architectures
  • A fun, passionate and collaborative workplace
  • Competitive salary and benefits, including equity


Why Zscaler?
People who excel at Zscaler are smart, motivated and share our values. Ask yourself: Do you want to team with the best talent in the industry? Do you want to work on disruptive technology? Do you thrive in a fluid work environment? Do you appreciate a company culture that enables individual and group success and celebrates achievement? If you said yes, we'd love to talk to you about joining our award-winning team.
Additional information about Zscaler (NASDAQ: ZS ) is available at https://www.zscaler.com .
Zscaler is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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Location

120 Holger Way, San Jose, CA 95134

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