Arista Networks is looking for a Lead Data Scientist/ML Architect to build and implement Machine Learning models for the huge amount of customer network data we collect. The ADE will work with other data scientists throughout the software development life cycle.
The role necessitates a team player’s abilities with a keen eye for detail and problem-solving skills. If you also have experience in Agile frameworks and popular Machine learning models, we’d like to meet you.
The role will involve leading various data science projects at Arista to glean value from both structured and unstructured data. The candidate will research, design, develop, and deploy machine learning models on production infrastructure. If the possibility of applying data modeling, classification, NLP, deep learning etc. to huge amounts of real-world data excite you, we want to talk to you.
Responsibilities:
Do exploratory analysis and build data science prototypes
Research, design, and implement appropriate ML algorithms and tools starting from raw data to deploying and refining models in production
Extend existing ML libraries and frameworks
Provide Architectural and Tech leadership in the team
Work with teammates, partners and clients to address pain points through data science
Produce clean, efficient code based on specifications
Integrate software components and third-party programs
Verify, deploy, Troubleshoot, debug, and upgrade the existing systems
Create technical documentation for reference, reporting, and evangelizing Arista’s data science initiatives in the industry.
Requirements:
Bachelor’s Degree in Computer Science from a four year college or university or related experience and/or training; or equivalent combination of education and experience. Master’s degree in machine learning is preferred.
7-8 years experience, and 3-4 years of applying machine learning to solve customer problems.
Deep knowledge and experience in using NLP techniques to solve real-world problems
Good Understanding of data structures, data modeling, and software architecture to build scalable and manageable infrastructure
Deep knowledge of math, probability, statistics and ML algorithms
Ability to write robust code in Python, Java, Scala, SQL, etc
Experience in Machine Learning Libraries and collaborating with other data scientists through notebooks.
Experience in working with large amounts of data, possibly stored in big data stores such as: Elastic, Cassandra, Hbase, Hive, HDFS, etc.
Experience in effective data exploration and visualization (e.g. Excel, Power BI, Tableau, Qlik, etc.)
Creative thinker and team player
Excellent communication skills
Resourcefulness and troubleshooting aptitude
Nice to Have:
Working experience in docker and K8s deployments
Working Experience in AWS/GCP
Working experience with Network technologies
Additional Information
All your information will be kept confidential according to EEO guidelines.
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