Data Scientist
$120K-$189K (Glassdoor est.)
About Netskope

Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security.

Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, San Francisco, Seattle, Bangalore, London, Melbourne, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at netskope.com/company/careers and follow us on Twitter @Netskope and Facebook.

Data Scientist


Within Netskope Engineering, the Security Services organization is responsible for building core security products and features, such as Data Loss Prevention, Malware and Threat Prevention, Cloud Confidence Index, Breach and Anomaly Detection. We apply Artificial Intelligence and Machine Learning technologies across Netskope cloud security platform. We are looking for talented data scientists with security domain knowledge. A successful candidate has deep technical expertise in applying AI/ML technologies in security applications and/or adjacent domains, ideally has been through the entire lifecycle of an award winning security product, and must be passionate about cloud security. You will have the opportunity to work with a team of talented engineers, researchers and data scientists to solve the most challenging cloud security problems.

Responsibilities:
Identify strong AI/ML use cases in cloud security, data security and adjacent domains, leveraging Netskope's rich set of data sources;
Define scalable data acquisition and labeling strategy for specific use cases;
Work with data engineers to retrieve, clean and normalize data. Ensure scalable and continuous high-quality data stream;
Work closely with threat research and development team in feature engineering. Make sure high-quality feature sets are chosen in a systematic way;
Select ML models for defined use cases. Implement KPIs to ensure optimal algorithms and results;
Conduct strict internal testing to ensure high efficacy, low false positive and false negative rate;
Interpret results and communicate findings;
Document use case, data acquisition, feature engineering, training, validation, deployment, future improvement opportunity and other important aspects;
Work closely with development and QE team in productization;
Be an evangelist of AI/ML within Netskope. Promote AI/ML wherever applicable, beyond security use cases;
Collaborate with data analytics team to define new platform requirements and continuously improve our horizontally scalable data lake.
Qualifications/Requirements:


First of all, must have true startup spirit. Be willing to wear multiple hats and deliver end-to-end;
Ability of thinking out-of-box and evaluating results based on customer value;
5+ years of industry experience in applying AI/ML, preferably on well-known security products or services, such as malware detection, anomaly detection, security analytics and data security;
Experience of applying AI/ML in more than one domains highly desirable;
Hands-on experience with relevant technology stacks such as CUDA, Python, R, Spark, Flink, Tensorflow;
Hands-on experience using modern big data pipeline;
Natural language process (NLP) and data mining experience highly desirable;
Security research experience and strong security domain knowledge highly desirable;
Energetic self-starter, with the desire to work in a dynamic fast-paced environment;
Excellent verbal and written communication skills;
Ability to influence without authority
Education:


PhD in Computer Science, Statistics, Electrical Engineering or equivalent technical degree.
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