Description

About Aragen Life Sciences Aragen Life Sciences Limited is a global R&D and manufacturing partner to the life sciences industry, supporting the full drug development lifecycle. With over 20 years of expertise, Aragen delivers innovative solutions across early-stage discovery, development, and manufacturing of new molecular entities. Driven by the purpose “In every molecule is the possibility for better health”, Aragen partners with global pharma and biotech organizations to transform scientific innovation into real-world health impact Job Summary Aragen Life Sciences is seeking a highly motivated Data Science Specialist with a strong research-oriented mindset to work on AI-driven Drug Discovery (AIDD) initiatives. The role focuses on developing end-to-end AI products using Generative AI, Computational Chemistry, and Advanced Data Science techniques to accelerate drug discovery and development. Key Responsibilities AI & Model Development Design and develop AI/ML models with a strong understanding of functional and non-functional requirements Build and fine-tune Generative AI models for drug discovery and life sciences applications Apply deep learning, reinforcement learning, and large language models (LLMs) in real-world projects Data Engineering & Processing Design and manage data pipelines for AI model training Perform data collection, cleaning, preprocessing, and feature engineering Ensure high data quality, reproducibility, and scalability Algorithm Optimization Optimize AI algorithms through hyperparameter tuning, model compression, and performance optimization Implement advanced optimization techniques for efficient model execution Security & Compliance Implement data security and privacy controls, including encryption and access management Ensure compliance with data protection and regulatory standards Collaboration & Deployment Collaborate with Business, Data Engineering, and DevOps teams Support the design, deployment, monitoring, and maintenance of end-to-end AI products Follow Agile methodologies using Azure DevOps Required Qualifications Doctorate (Ph.D.) in Data Science, Computational Chemistry, Bioinformatics, Life Sciences, or related fields Strong foundation in algorithms, data structures, and problem-solving Minimum 2 end-to-end AI/ML projects completed Technical Skills Core Expertise Strong hands-on experience with Machine Learning, Deep Learning, Reinforcement Learning, and LLMs Expertise in AI-Driven Drug Discovery (AIDD) using Cheminformatics and Bioinformatics libraries Experience in Generative & Computational Chemistry Tools & Frameworks PyTorch, Keras, MLflow Jupyter Notebook, VS Code, PyCharm Relational databases (Microsoft SQL Server preferred) Azure DevOps (Agile workflows) Key Skills Generative AI • AIDD • Machine Learning • Deep Learning • PyTorch • Keras • Cheminformatics • Bioinformatics • MLflow • Azure DevOps • SQL

Role and Responsibilities

• Key Responsibilities AI & Model Development Design and develop AI/ML models with a strong understanding of functional and non-functional requirements Build and fine-tune Generative AI models for drug discovery and life sciences applications Apply deep learning, reinforcement learning, and large language models (LLMs) in real-world projects Data Engineering & Processing Design and manage data pipelines for AI model training Perform data collection, cleaning, preprocessing, and feature engineering Ensure high data quality, reproducibility, and scalability Algorithm Optimization Optimize AI algorithms through hyperparameter tuning, model compression, and performance optimization Implement advanced optimization techniques for efficient model execution Security & Compliance Implement data security and privacy controls, including encryption and access management Ensure compliance with data protection and regulatory standards Collaboration & Deployment Collaborate with Business, Data Engineering, and DevOps teams Support the design, deployment, monitoring, and maintenance of end-to-end AI products Follow Agile methodologies using Azure DevOps