What are the responsibilities and job description for the Senior ML Engineer/Data Scientist (ZDX) position at Zscaler?
Our Engineering team built the world’s largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy.
We're looking for an experienced Senior Data Scientist to join our Digital Experience AI/analytics platform (ZDX) team. Reporting to the Sr. Manager, Machine Learning, you will play a pivotal role in developing innovative data science solutions to enhance user digital experiences. This role is based in our San Jose, CA office (hybrid, 3 days a week in office). In this role, you’ll be responsible for:
- Leading the identification and resolution of performance issues by building models to pinpoint root causes of poor user experiences and detect performance bottlenecks for individual users or cohorts.
- Designing, training, and deploying predictive models to forecast system performance, user behavior, and potential friction points in the digital experience.
- Implementing advanced AI/ML algorithms to detect and predict anomalies across multi-dimensional datasets, particularly time series.
- Managing the entire lifecycle of machine learning projects, from analysis and training to deployment in production environments.
- Creating compelling data visualizations to communicate actionable insights to both technical and non-technical audiences.
What We’re Looking For (Minimum Qualifications)
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- 3 years of professional experience in data science or related roles.
- Proficiency with tools and platforms such as Python, TensorFlow, SQL, and relevant libraries. Familiarity with Generative AI and NLP techniques.
- Expertise in multi-dimensional anomaly detection algorithms with a focus on time series data as well as experience with networking and end-point observability systems.
- Demonstrated success in building and deploying ML models in production environments, including orchestration using tools like Kubernetes and Airflow.
What Will Make You Stand Out (Preferred Qualifications)
- Knowledge of network troubleshooting, including familiarity with protocols like HTTP, TCP, and ICMP.
- Published research or contributions to the digital experience, end-user observability, or data science community.
- Demonstrated expertise in user experience metrics, monitoring tools, and methodologies within the monitoring space.
