Senior Data Scientist

United States

Full Time Senior-level / Expert USD 68K - 135K *
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Cohesity

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Cohesity is on a mission to radically simplify how organizations manage their data to unlock limitless value. We make it easy to back up, manage and derive value from data while protecting data against ransomware attacks. At Cohesity, we’re encouraged to think big and we take on dynamic goals that require innovative thinkers. Obsession with our customers keeps us humble and drives us to keep learning.

We’ve been named a Leader by multiple analyst firms, and are prominently featured in the Forbes Cloud 100 and CRN’s Coolest Cloud companies.

About This Role:

At Cohesity, we are building the next generation data management and analytics platform as a service, a first of its kind in the industry. This builds upon the unique tech stack Cohesity is known for. Join us and help make the first release for a major company initiative.  This is an amazing opportunity for a hands-on, experienced Data Scientist with a track record of achieving tangible outcomes.

Responsibilities:

  • Provide technical leadership, and mentoring to team members
  • Work with product managers to understand customer requirements and design and deliver cloud SaaS services
  • Perform the role of Data Scientist within the team, designing and building Machine Learning Models to help us achieve better insights and outcomes
  • Work with functional leads to understand their data requirements and design and deliver data pipelines to scale to billions of events
  • Collaborate with operations to establish KPIs for different services and own the end-to-end delivery and lifecycle management
  • Establish core data management principles and best practices

What we are looking for:

  • MS/PhD in Computer Science or a related software field
  • 5+ years of relevant experience building machine learning/statistical models in a SaaS environment
  • We run on all major public clouds; familiarity with at least one is required (AWS, GCP, or Azure)
  • Experience with data lakes and data-warehouses. BigQuery, Snowflake or Redshift experience preferred. 
  • Experience in either streaming or batch ETL pipelines preferred. Experience with Kafka and Spark preferred.
  • Experience with microservices and containers.
  • Experience in either Elasticsearch or Solr is helpful.
  • Experience with cloud native Machine Learning service a big plus.
  • Experience in NoSQL engines a plus.
  • Strong analytical and problem-solving skills
  • Hands on coding skills in Golang, Python or Java
  • Knowledge in Storage, Filesystems or Data Protection domain is a plus
  • Motivated to solve complex problems and challenges. 
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Equal Employment Opportunity Employer (EEOE)

Cohesity is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status or any other category protected by law. 

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact us at 1-855-9COHESITY or talent@cohesity.com for assistance.

 

COVID-19

Cohesity requires all employees who enter its U.S. offices to be fully vaccinated against the COVID-19 virus and to provide documented proof thereof. Cohesity will comply with applicable law regarding the reasonable accommodation of individuals who are not vaccinated because of a sincerely held religious belief, disability or medical condition. This vaccination requirement does not apply to employees who work remotely and do not enter Cohesity offices.

* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net
Job perks/benefits: Team events
Job region: North America
Job country: United States
Job stats:  2  0  0

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