In the ever-evolving field of data science and artificial intelligence, the role of a Generative AI Data Scientist stands as a beacon of innovation and problem-solving. The first round of interviews with Rohini Jain embarks on a journey to explore the depths of fundamental concepts, practical experience, and hands-on expertise. The interviewer, Rahul Saxena, seeks to unravel the knowledge and insights that Rohini brings to the table.Rohini Jain, a seasoned professional in the realm of data science, brings to the forefront a wealth of experience and expertise. With proficiency in multiple programming languages and a strong foundation in statistical platforms such as Python, Java, and MATLAB, Rohini is well-equipped to navigate the complex landscape of data-driven solutions. Her hands-on experience with Python packages like pandas, scikit-learn, TensorFlow, numpy, SparkML, and NLTK adds a layer of depth to her skill set, making her a valuable asset in the world of data science.Rohini's journey as a Generative AI Data Scientist has seen her design NLP/LLM applications and products, explore state-of-the-art models and techniques, and conduct intricate machine learning experiments. Her ability to deploy REST APIs, create minimalistic UIs using Docker and Kubernetes, and showcase NLP/LLM applications through web frameworks like Dash, Plotly, and Streamlit is a testament to her practical knowledge and proficiency.Furthermore, Rohini's commitment to building modular AI/ML products that can be consumed at scale and her expertise in designing and developing flexible, scalable, and extensible enterprise solutions showcase her versatility and adaptability in tackling complex challenges. Education plays a pivotal role in Rohini's journey, with a Bachelor's or Master's degree in Computer Science, Engineering, Maths, or Science serving as the foundation. Her engagement in modern NLP MOOC courses and open competitions further underscores her commitment to continuous learning and growth. As we delve into this first round of interviews, we aim to uncover the wealth of knowledge and experience that Rohini Jain brings to the role of a Generative AI Data Scientist. From fundamental concepts to practical applications, this interview series promises to shed light on the intricacies of this dynamic field.
Detail about Real Job posting:

Role: Generative AI Data Scientist.

Location: Mumbai, New Delhi, Pune, Chennai, Bangalore, New York, London.

Job Description:

- Demonstrated proficiency in multiple programming languages with a strong foundation in a statistical platform such as Python, Java, or MATLAB.
- Experience with Python packages like pandas, scikit-learn, TensorFlow, numpy, SparkML, NLTK is Highly Desirable.
- Design NLP/LLM applications/products by following robust coding practices.
- Explore SoTA models/techniques so that they can be applied for automotive industry usecases.
- Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions.
- Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools.
- Showcase NLP/LLM applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc. ).
- Build modular AI/ML products that could be consumed at scale.
- Design & develop enterprise solutions to be flexible, scalable & extensible.
- Developing Knowledge graphs, Graphs Analytics - tools.
- Improve complex data flow, data structures and database design to move to next platform.
- Build solutions that incorporate numerical techniques such as linear algebra, machine leaning, statistics, and optimization.
- Be a Role Model to the team to collaborate on good object-oriented designs & domain modeling.
- Develop areas of continuous and automated deployment.
- Introduce and follow good development practices, innovative frameworks, whitepapers and technology solutions that help business move faster.
- Enforce good agile practices like test driven development, Continuous Integration.
- Follow best practices like estimation, planning, reporting and improvement brought to processes in every day work.
- Stakeholder management, understanding the requirement and building roadmaps.
- Experience in team management, mentoring data scientists.
- Developing Knowledge graphs, Graphs Analytics – tools.
Desired Experience: 5+ Years.

Education: Bachelors or Master s Degree in Computer Science, Engineering, Maths or Science.
Performed any modern NLP MOOC courses/open competitions is also welcomed.
Employment Type: Full Time, Permanent.

Role Category: Data Science & Machine Learning.