Customer Success Manager

About Concentric:

Join the journey to reinvent data security. Concentric, a next generation AI data security start-up, is helping enterprises discover and protect their business-critical data. We are growing fast and expanding rapidly. Our core values are: Trust, Humility, Learning.

Location: Pune

About the openings:

The role will be part of our customer success team. You will work extensively on large datasets to identify and help remediate data risks for customers from diverse domains, and support them as a trusted security advisor.

Responsibility

• Analyse customer data on Concentric Platform, extract relevant insights to identify data risks, develop risk remediation strategies
• Prepare and present data risk reports to customers. Handhold them for implementation of the risk remediation strategies
• Label large datasets for supervised learning of AI models
• Serve as customer’s trusted data security advisor, providing subject matter expertise, strategic guidance to drive adoption of concentric platform aligned with customer objectives

Preferred Qualification & Skills

• Strong experience on with data analytics. Proven ability to extract relevant insights from big volumes of data to solve specific problems. Eye for detecting trends, anomalies in data.
• Customer advisory experience preferably in data security domain
• Experience on with Excel as data analysis and reporting tool is required. Knowledge of other tools like Python, Kibana, Jira, ppt will be a plus.
• Proven team leadership skills
• Broad knowledge of operationalizing data security, regulations and standards will be an advantage
• Excellent communication skills across various formats and mediums. Strong presentation and facilitation skills
• Use creative problem-solving skills to help customers reach their business goals and maximize the value they are getting from Concentric platform
• Graduate/Post Graduate in Engineering discipline from premium institute
• Experience on developing training datasets for AI models and data labelling for supervised learning of AI models.