Job
Description
Mist, a Juniper Company, is the first vendor to bring an enterprise-grade full stack (AP, switch and route) cloud AIOps solution that is a leader in the Gartner wired / wireless MQ. On top of this real time cloud stack, we are building an AI-empowe'red platform to answer questions on par with network domain experts and automate remediation to poor user experiences on the network. Mist s Marvis AI/ML platform has become the new global standard for many fortune 500 companies. The mission of the Data Science team at Mist is to leverage state-of-art ML and AI technologies to build the next-generation self-driving network solution that can deploy and operate networks faster and on par with human IT domain experts. The team includes a group of experienced and talented data scientists and data science engineers, and builds the end-to-end data analytics infrastructure and ML models of the product. We are looking for a Data Scientist to help define and expand this mission. As a data scientist in the Mist Data Scientist team, you will collaborate with product managers, customer and domain experts to identify use-impacting real customer problems, use your deep DS/ML knowledge to develop models to help predict user experience and find root cause to user experience problems, and work closely with data engineers to implement and scale the models in a production SaaS cloud environment. Responsibilities Collect, clean, and transform data from various sources and formats for model training Perform exploratory data analysis and visualization to understand patterns and trends Build, test, and deploy predictive models and algorithms using appropriate tools and frameworks to a production cloud environment Communicate findings and recommendations to stakeholders and clients using clear and compelling reports and presentations Collaborate with other data scientists, engineers, and domain experts on cross-functional projects Qualifications / Requirements Masters or PhD in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background Proficiency in Python, R, SQL, or other programming languages for data analysis Experience with data wrangling, manipulation, and visualization tools and libraries such as pandas, numpy, scikit-learn, matplotlib, seaborn, etc Knowledge of machine learning concepts and techniques such as supervised and unsupervised learning, regression, classification, clustering, dimensionality reduction, etc Familiarity with cloud computing platforms and services such as AWS, Azure, or Google Cloud Strong analytical and problem-solving skills
