Data Analytics Expert

4 days ago


Pune, Maharashtra, India Concentric AI Full time
About Concentric AI
Concentric AI is a cutting-edge data security solution that protects business-critical content across on-premises and cloud-based data stores. Our innovative approach uses deep learning to accurately categorize structured and unstructured data, assess risk, and remediate security issues.

We are headquartered in San Mateo, California, and backed by leading Silicon Valley VCs. Our core values of Trust, Humility, and Learning guide our interactions with colleagues, partners, and customers.

The role you will be joining is part of the Metrics, Insights, and Data (MIND) team, which drives all data-related efforts at the company. As a key member of this team, you will:
  1. Analyze customer data on the Concentric AI platform to extract relevant insights and identify data risks.
  2. Develop, curate, and maintain training datasets for AI models.
  3. Explore, annotate, and label large datasets for supervised learning of ML models.
  4. Work closely with AI and software development teams to drive automation.
  5. Serve as a data subject matter expert and partner with Customer Success to drive adoption of the Concentric AI platform.

Your Responsibilities
You will be responsible for analyzing customer data to extract relevant insights and identifying data risks. You will also develop, curate, and maintain training datasets for AI models, explore, annotate, and label large datasets for supervised learning of ML models, and work closely with AI and software development teams to drive automation. Additionally, you will serve as a data subject matter expert and partner with Customer Success to drive adoption of the Concentric AI platform.

Requirements
To succeed in this role, you will need strong experience and expertise in data analytics, including proven ability to extract relevant insights from large volumes of data to solve specific problems. You will also need a keen eye for detecting trends, anomalies, and patterns in data. Experience developing training datasets, data annotation, and labeling for supervised learning of AI/ML models is essential. Knowledge of Python, scripting, visualization, or analytics tools is a plus, as well as experience with data governance in a large enterprise setting and data catalog tools like Collibra. A broad knowledge of data security, regulations, and standards is an advantage.

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