Senior Staff Data Scientist
Framingham, MA, USA | Huawei
Industry:Telecommunications & Wireless
Functions:IT / Information Technology
Job Description:71 people have viewed this job
We have multiple exciting positions in AIOps (Artificial intelligence for IT Operations) and Intelligent Storage Systems, utilizing big data, modern machine learning and other advanced analytics technologies to enhance IT operations functions with proactive, personal and dynamic insight, as well as leveraging AI inside the IT especially storage systems so that the system can make smart management decisions. The software we are working on will enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and visualization technologies. You will work with a team of experts in researching and developing innovative solutions that utilize existing and emerging technologies to add substantial value to Huawei enterprise and public cloud customers.
The role of the architect is to apply different machine learning, deep learning etc. AI algorithms to different AIOps and Intelligent Storage System use cases; research; involve in development of big data infrastructure and applications; design, prototype and develop cutting-edge solutions for AIOps and the next generation of AI-driven intelligent storage systems using the state-of-art technologies; play a significant role in strong engineering teams to deliver key and high quality software products/capabilities, influence future direction of the industry via innovations to solve some of the technology challenges.
Define AI use cases for Huawei IT and storage products, provide data science guideline to the team
Research and develop machine learning and deep learning algorithms for AIOps and intelligent systems, evaluate algorithms’ effectiveness and performance, and optimize algorithms for real-time performance
Selecting features, building and optimizing classifiers using machine learning techniques
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
Creating automated anomaly detection systems and constant tracking of its performance
Responsible for Huawei AIOps and Intelligent Storage System architecture design which focuses on AI-driven, automation, scalability, serviceability, and ease-of-use.
Work with chief architects and other subject experts to execute technical plan and technical roadmap which describes the next generation of Huawei AIOps and Intelligent Storage System architecture and features for the next 2-5 years
Involve in full stack software development for AIOps projects/products including data collection, data process, big data, machine learning services and visualization technologies by using state-of-art technologies including development/deployment in cloud, containers, microservice, Hadoop, NoSQL, large scale messaging systems, machine learning services, and visualization of big data
Is encouraged to research and prototype advanced and/or emerging technologies to solve real customer issues and propose innovative ideas and projects
Work in a team environment by following Agile software development process
Requirements for position
A MS/PhD degree in Computer Science, Mathematics or other technical major
5+ year hands-on AI industry experiences building machine learning, deep learning solutions.
5+ year experiences with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano, H20, etc.)
Excellent understanding of machine learning and deep learning techniques, algorithms and best practice principles
Experience writing software in one or more ML languages such as Python, Scala, R and/or similar
Real plus if experienced in development of AI-driven solution for IT platform or systems
Experience in full technology stack for Big Data: data layer, data processing, data ingestion, data presentation, operation, scheduling, security and governance
Experience in analytics tools and environment for Big Data: such as Hadoop, Spark, Pig, Hive, MapReduce, Flume, SQL
Experience in performance tuning for machine learning services
Good applied statistics skills, such as distributions, statistical testing, regression, etc.
Plus if experienced in data visualization tools, such as D3.js, GGplot, etc.