Data Science Specialist

Data Science Specialist

Responsibilities:

- Design and develop AI models with a strong understanding of non-functional requirements.

- Implement robust and scalable AI solutions in the following areas:

• Model Development: Develop and fine-tune generative AI models for various applications, ensuring efficiency and high-quality outputs.
• Data Processing: Design and manage data pipelines for training and deploying AI models, including data collection, cleaning, and preprocessing.
• Algorithm Optimization: Analyze and optimize AI algorithms for performance, including tasks like hyperparameter tuning, model compression, and implementing advanced optimization techniques.
• Prompt Engineering: Design and optimize prompts for generative AI models to improve performance and output quality, experimenting with different prompt structures and techniques.
• Security Measures: Implement security measures to protect sensitive data and AI models, including data encryption, access control, and ensuring compliance with data privacy regulations.



- CADD and AI-driven Drug Discovery:

• Utilize CADD techniques such as molecular docking, virtual screening, and quantitative structure-activity relationship (QSAR) modelling. Apply AI-driven approaches for target identification, hit identification, ADMET prediction, lead optimization, and drug repositioning
• Maintain and improve existing AI models and pipelines.
• Collaborate with cross-functional teams to define, design, and deploy new AI features using Azure DevOps for CI/CD pipeline.
• Write unit tests and use debugging tools to ensure the robustness and reliability of AI models.
• Work on bug fixing and improving AI model performance.

Qualifications:

- 5-7 years of experience in data science and AI, with a minimum of 5 end-to-end AI projects delivered.

- Hands-on experience with data science tools like Jupyter, Spyder, Visual Studio Code, and PyCharm.

- Experience with Generative AI models and techniques such as GANs, VAEs, and transformers.

- Experience with relational databases like Microsoft SQL Server and NoSQL databases.

- Experience with version control tools like Git.

- Strong problem-solving skills, algorithmic skills, and data structures.

- Experience in Agile methodologies using Azure DevOps is a plus.

- Proficiency in CADD techniques and AI-driven discovery methods