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• No of position :- ( 1 )

• Post :- 29th Mar 2024

We are seeking a highly skilled and motivated Generative AI Data Scientist to join our dynamic team. As a Generative AI Data Scientist, you will be responsible for leveraging cutting-edge techniques in Natural Language Processing (NLP), Generative AI (GEN-AI), and Python programming to drive innovation in data tokenization processes. Your role will involve developing advanced algorithms and models to generate synthetic data, facilitating secure and privacy-preserving data sharing while maintaining data utility and integrity.

Key Responsibilities:

Research, design, and implement state-of-the-art algorithms and models for data tokenization and generation using Generative AI techniques.
Develop and optimize Natural Language Processing (NLP) models for text data tokenization and synthesis.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Conduct experiments, analyze results, and iterate on models to improve performance and efficiency.
Stay abreast of the latest advancements in Generative AI, NLP, and related fields, and incorporate relevant techniques into our data tokenization framework.
Work closely with data engineers and software developers to integrate developed models into production systems.
Ensure compliance with data privacy and security regulations throughout the development process.

Requirements:
Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
Proven experience in developing and deploying NLP models and Generative AI techniques.
Proficiency in Python programming language and libraries such as TensorFlow, PyTorch, or similar.
Strong understanding of data tokenization methods and techniques.
Familiarity with data privacy regulations and best practices.
Excellent problem-solving skills and ability to work independently as well as part of a team.
Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders.

Preferred Qualifications:
Experience working with large-scale datasets and distributed computing frameworks.
Knowledge of deep learning architectures and techniques.
Prior experience in the development of privacy-preserving AI solutions.
Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.