Data Science Manager at Zscaler

Short Description:

The Data Science Manager position at Zscaler in Bangalore involves leading an award-winning team in full-stack Machine Learning product development for cloud security, operations, and intelligence applications. Responsibilities include designing and implementing machine learning models for diverse use cases like threat detection and anomaly detection. The role requires a minimum of 12 years of industry experience in machine/deep learning frameworks, proficiency in Python and SQL, and excellent interpersonal and communication skills. Desired qualifications include expertise in public cloud services, ML automation platforms, programming languages like Go, and knowledge of networking and network security.

 

---

 

Position: Data Science Manager - Deep Learning, Machine Learning

Job Reference: REF7819I

Location: Bangalore, India

About Zscaler

Zscaler (NASDAQ: ZS) is a company dedicated to advancing digital transformation, enabling customers to become more agile, efficient, resilient, and secure. Zscaler achieves this through its cloud-native platform, the Zscaler Zero Trust Exchange, which safeguards numerous customers against cyberattacks and data breaches by securely connecting users, devices, and applications from any location.

With over a decade of experience in cloud development, operations, and scalability, Zscaler serves a global clientele, including 450 of the Forbes Global 2000 organizations. Besides protecting customers from damaging threats like ransomware and data breaches, Zscaler assists in reducing costs, simplifying operations, and enhancing user experiences by eliminating latency-inducing gateway appliances.

Established in 2007, Zscaler's mission is to create a secure and enjoyable cloud environment for enterprise users. Their purpose-built security platform deploys defenses and controls at the point of internet connection, ensuring that every connection is fast and secure, regardless of how and where users connect or where their applications and workloads are located.

Key Responsibilities:

As a Data Science Manager, you will be part of an award-winning team engaged in full-lifecycle full-stack Machine Learning product development, spanning from feature engineering to model development and evaluation.

Your work will involve diverse use cases, such as threat detection, malware detection, content classification, anomaly detection, and AIOps (advanced networking diagnosis), presenting the opportunity to explore various machine learning algorithms and tools. Your role will encompass designing and creating machine learning models to offer faster and more effective solutions for cloud security, cloud operations, and cloud intelligence applications.

While expertise in all stages of a Machine Learning project is not mandatory, a strong interest and curiosity in different aspects, from data to the business impact of models, are essential.

Required Qualifications:

• A degree in Machine Learning, Computer Science, or Electrical Engineering from a reputable institution (Ph.D. degree preferred but not mandatory).

• Passion for applying ML/AI to address real-world business challenges, improving security, and business outcomes.

• A minimum of 12 years of industry experience in one or more machine/deep learning frameworks.

• A minimum of 12 years of industry experience with Python and SQL.

• Outstanding interpersonal, technical, and communication skills.

• Strong business acumen.

• Ability to quickly learn, evaluate, and adopt new technologies.

• Capability to lead and execute projects from inception to completion.

• A solid foundation in computer science.

Desirable Skill Sets:

• A minimum of 12 years of professional experience.

• Experience with various public cloud services (e.g., AWS, Google, Azure) and ML automation platforms (e.g., Kubeflow).

• Familiarity with various programming languages, such as Go.

• Good understanding of operating systems and distributed systems.

• Knowledge of networking and network security.

Please click here to apply.