As a Data Scientist, you will leverage your expertise in Machine Learning, Deep Learning, Computer Vision, Natural Language Processing and Generative AI to develop innovative data-driven solutions and applications. You will play a key role in designing and deploying dynamic models and applications using modern web frameworks like Flask and FastAPI, ensuring efficient deployment and ongoing monitoring of these systems.

Key Responsibilities :

- Model Development and Application : Design and implement advanced ML and DL models.

- Develop web applications for model deployment using Flask and FastAPI to enable real-time data processing and user interaction.

- Data Analysis : Perform exploratory data analysis to understand underlying patterns, correlations and trends. Develop comprehensive data processing pipelines to prepare large datasets for analysis and modeling.

- Generative AI : Employ Generative AI techniques to create new data points, enhance content generation and innovate within the field of synthetic data production.

- Collaborative Development : Work with cross-functional teams to integrate AI capabilities into products and systems. Ensure that all AI solutions are aligned with business goals and user needs.

- Research and Innovation : Stay updated with the latest developments in AI, ML, DL, CV and NLP. Explore new technologies and methodologies that can impact our products and services positively.

- Communication : Effectively communicate complex quantitative analysis in a clear, precise and actionable manner to senior management and other departments.

Required Skills and Qualifications :

- Education : BE or Masters or PhD in Computer Science, Data Science, Statistics or a related field.

- Experience : 15+ years and 7+ years of relevant experience in a data science role with a strong focus on ML, DL and statistical modeling.

- Technical Skills : Strong coding skills in Python, including experience with Flask or FastAPI. Proficiency in ML, DL frameworks (e.g., PyTorch, TensorFlow), CV (e.g., OpenCV) and NLP libraries (e.g., NLTK, spaCy).

- Generative AI : Experience with generative models such as GANs, VAEs or Transformers.

- Deployment Skills : Experience with Docker, Kubernetes and continuous integration/continuous deployment (CI/CD) pipelines.

- Strong Analytical Skills : Ability to translate complex data into actionable insights.

- Communication : Excellent written and verbal communication skills.

- Certifications : Certifications in Data Science, ML or AI from recognized institutions is added advantage.