Senior Data Scientist

Overview

Cohesity is a leader in AI-powered data security and management. Aided by an extensive ecosystem of partners, Cohesity makes it easy to secure, protect, manage, and get value from data — across the data center, edge, and cloud. Cohesity helps organizations defend against cybersecurity threats with comprehensive data security and management capabilities, including immutable backup snapshots, AI-based threat detection, monitoring for malicious behavior, and rapid recovery at scale.

We’ve been named a Leader by multiple analyst firms and have been globally recognized for Innovation, Product Strength, and Simplicity in Design.

Join us on our mission to shape the future of our industry.

Cohesity is seeking a highly skilled and motivated data scientist to join our growing team. In this role, you will be instrumental in developing and deploying advanced analytics and machine learning models to enhance our data protection capabilities, optimize system performance, and provide deeper insights into security threats and data trends. You will work with complex data sets, applying your expertise in machine learning, algorithms, and mathematics to solve challenging problems in the realm of enterprise data security.

We are looking for someone who is not only technically solid, but also possesses a strong eagerness to learn, thrives on solving complex problems by thinking out of the box, and has a clear bias towards action.

• Design, build, deploy, and maintain robust machine learning pipelines for various data protection applications (e.g., anomaly detection, threat prediction, data classification, behavioral analytics).
• Develop and implement advanced algorithms to analyze vast datasets, identify patterns, and extract actionable insights.
• Collaborate closely with engineering and product management to develop proof‑of‑concept implementations that shape future product features.
• Stay abreast of relevant conference publications, competitive analyses and best industry practices, extracting key insights and informing team strategies.
• Communicate complex analytical findings and recommendations clearly and concisely to technical and non‑technical stakeholders.

• Master’s degree in computer science or a doctorate in a STEM discipline (e.g., Mathematics, Statistics, Physics, Engineering).
• Solid understanding of the statistical and mathematical foundations of machine learning algorithms, and the ability to translate them into real‑world solutions.
• Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support decision making.
• Proficiency in at least one programming language used for ML (Python or Java).
• Experience with common ML libraries (e.g., Scikit‑learn, Pandas, PyTorch, Matplotlib etc.).
• Experience with building ML pipelines on cloud platforms (e.g., AWS, Azure, GCP).
• Strong problem‑solving skills and the ability to work independently as well as part of a collaborative team.
• Experience publishing research (e.g., in peer‑reviewed journals or conference proceedings) in STEM fields and presenting at relevant events.
• Familiarity with Big Data technologies (e.g., Spark, Hadoop) is good to have, but not a must.

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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 1-855-9

COHESITY or  for assistance.

Cohesity employees who are within a reasonable commute (e.g. within a forty‑five (45) minute average travel time) work out of our core offices 2‑3 days a week of their choosing.

Interested candidates based outside of the designated areas are welcome to apply, provided they have the right to work in the job location.