What are the responsibilities and job description for the Sr. Data Scientist position at Cohesity?
Job Description:
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 datasets, 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.
Responsibilities:
• 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 industry best
practices, to extract key insights and to inform team strategies.
• Communicate complex analytical findings and recommendations clearly and concisely to
technical and non-technical stakeholders.
Required Qualifications:
• 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.
• Proficiency in at least one programming language used for ML (Python, R or Java).
• Experience with common ML libraries (e.g., Scikit-learn, Pandas, PyTorch, Matplotlib etc.).
Preferred Qualifications:
• 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.