Onsite Senior Data Scientist — AI/Datacenter ML Lead

Hobbsnews; Sunnyvale, Northern (CA, KY); Hybrid; USD 154,000 - 311,000; Full time

Job summary

Hewlett Packard Enterprise seeks a Senior Data Scientist to lead data-science research and software development for the AI Datacenter and autonomous platform. The role focuses on leveraging big data, building scalable ML models, and enhancing the Mist platform and cloud intelligence for Marvis.

Based onsite in California, you will collaborate with engineers to design real-time anomaly detection, RCA, and predictive analytics across large-scale networks, applying time-series analysis and advanced

Qualifications

• Bachelor's degree or equivalent in CS/Engineering/Math.
• 5+ years of experience in Search Indexing, Ranking, Information Retrieval and Querying.
• Proficient in Python and Golang and deploying NLP/ML models at scale.
• Solid statistics and math background; ML methods like k-NN, Naive Bayes, SVM, and trees.

Responsibilities

• Design and implement ML solutions processing terabytes of streaming data to detect anomalies and predict trends.
• Troubleshoot production environment and multi-cloud data processing engines.
• Develop scalable data processing pipelines using open-source tools and cloud DevOps practices.

Skills

Python

Golang

NLP

Machine Learning

Information Retrieval

Time Series

Education

Bachelor's degree in CS/Engineering/Mathematics

PhD in Statistics/Operations Research/CS or equivalent

Tools

Apache Spark

Apache Storm

Apache Flink

Hadoop

Hive

Elasticsearch

Redis

Job description

Hewlett Packard Enterprise seeks a Senior Data Scientist to lead data-science research and software development for the AI Datacenter and autonomous platform. The role focuses on leveraging big data, building scalable ML models, and enhancing the Mist platform and cloud intelligence for Marvis.

Based onsite in California, you will collaborate with engineers to design real-time anomaly detection, RCA, and predictive analytics across large-scale networks, applying time-series analysis and advanced