Sr/ Staff/Sr. Staff/ Principal Engineer (Machine Learning | Data Science | Python)

About Zscaler 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 The ZPA Advanced Analytics team at Zscaler is looking for a data scientist who will help us in the analysis of vast amounts of data. The primary focus will be on data mining, statistical analysis and developing ML-based tools that would be deployed on product-grade systems. Responsibilities

• Data mining using state-of-the-art methods
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Ad-hoc analysis and presenting your results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance

Skills and Qualifications

• BTech/MTech in CSE or relevant field from a reputed university.

5+ years of experience in developing and deploying ML applications. Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Excellent proficiency in Python. Experience with common data science toolkits, such as NumPy, SciPy or similar frameworks. Great communication skills. Proficiency in using query languages such as SQL. Experience with NoSQL databases, such as MongoDB, Cassandra.

• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Working knowledge of AWS Cloud .
• Knowledge of Agile methodology and Jira.
• Knowledge of versioning systems like BitBucket and Git.
• Basic understanding of PySpark, Kafka.

#LI-MS6 By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines. Zscaler is proud to be an equal opportunity and affirmative action employer. We celebrate diversity and are committed to creating an inclusive environment for all of our employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status or any other characteristics protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link. Pay Transparency Zscaler complies with all applicable federal, state, and local pay transparency rules. For additional information about the federal requirements, click here . Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. #J-18808-Ljbffr