Director - Data Science

Director - Data Science

• Job Title: Data Scientist
• Position Summary:
• As a Data Scientist at FSL, 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 Master’s or PhD in Computer Science, Data Science, Statistics or a related field.
• Experience: 5 to 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.