Associate Director Data Science

Job Description

Summary Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the definition, implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or creation through enrichment, consumption, retention, and retirement, enabling the availability of useful, clean, and accurate data throughout its usefull lifecycle. High agility to be able to work across various business domains. Integrate business presentations, smart visualization tools and contextual storytelling to translate findings back to business users with a clear impact.Independently set strategy, manage budget, ensuring appropriate staffing and coordinating projects within the area supervised. If managing a team: empowers the team and provides guidance and coaching, with limited guidance from more senior managers. About The Role Position Title: Associate Director Data Science Location – Hyd-India Hybrid About The Role We are seeking a highly skilled Data Science Architect to design and implement cutting-edge Data Science / Generative AI (GenAI) solutions tailored for the pharmaceutical and life sciences industry . This role will be responsible for defining AI strategies, selecting and fine-tuning generative AI models, and ensuring seamless integration with enterprise systems to enhance drug discovery, clinical trials, regulatory compliance, and patient-centric solutions. The AI/GenAI Architect will collaborate closely with data scientists, engineers, and business stakeholders to develop scalable, compliant, and high-performance AI applications that leverage large language models (LLMs), multimodal AI, and AI-driven automation . Your Responsibilities Include But Are Not Limited To GenAI Strategy & Roadmap: Define and implement a generative AI architecture and roadmap aligned with business goals in pharma and life sciences. Solution Design: Architect scalable GenAI solutions for drug discovery, medical writing automation, clinical trials, regulatory submissions, and real-world evidence generation. LLM Development & Optimization: Work with data scientists and ML engineers to develop, fine-tune, and optimize large language models (LLMs) for life sciences applications, such as scientific literature analysis, regulatory intelligence, and patient engagement. Cloud & On-Prem AI Infrastructure: Design GenAI solutions leveraging cloud platforms (AWS, Azure, GCP) or on-premise infrastructure while ensuring data security and regulatory compliance. MLOps & Deployment: Implement best practices for GenAI model deployment, monitoring, and lifecycle management within GxP-compliant environments. Compliance & Governance: Ensure GenAI solutions comply with regulatory standards (FDA, EMA, GDPR, HIPAA, GxP, 21 CFR Part 11) and adhere to responsible AI principles, including bias mitigation and explainability. Performance Optimization: Drive efficiency in generative AI models, ensuring cost optimization and scalability while maintaining data integrity and compliance. Stakeholder Collaboration: Work with cross-functional teams, including platform teams, and Drug Development teams, to align GenAI initiatives with enterprise and industry-specific requirements. Research & Innovation: Stay updated with the latest advancements in GenAI, multimodal AI, AI agents, and synthetic data generation to incorporate emerging technologies into the company’s AI strategy. What You’ll Bring To The Role: Experience in GenAI applications for medical writing, automated clinical trial protocols, drug discovery, and regulatory intelligence. Knowledge of AI explainability, retrieval-augmented generation (RAG), knowledge graphs, and synthetic data generation in life sciences. AI/ML certifications from AWS, Google, or Microsoft. Understanding of biomedical ontologies, semantic AI models, and federated learning. Exposure to fine-tuning the LLM models will be a big plus Exposure to SLM or domain LLM model will be a big plus. BioGPT & PubMedBERT: NLP for biomedical literature and clinical trial analysis. Custom SLMs: Fine-tune Mistral 7B, Phi-2, or Gemma on pharma datasets MLOps & DevOps: Familiarity with CI/CD, containerization (Docker, Kubernetes), vector databases, and real-time model monitoring. Regulatory & Ethical AI: Understanding of AI governance, responsible AI principles, and compliance requirements for GenAI in pharma. Problem-Solving: Strong analytical and problem-solving skills with the ability to design innovative GenAI solutions for life sciences use cases. Communication & Leadership: Excellent communication skills to articulate GenAI strategies and solutions to technical and non-technical stakeholders. Desirable Requirements: Bachelor's or Master's degree in Computer Science, AI, Data Science, Bioinformatics, or a related field. Experience: 8+ years in AI/ML development with at least 2 years in an AI Architect or GenAI Architect role in pharma, biotech, or life sciences. Technical Expertise: Strong proficiency in Generative AI, large language models (LLMs), multimodal AI, and deep learning for pharma applications. Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, Scikit-learn, etc.). Experience with data engineering, ETL pipelines, and big data technologies (Spark, Kafka, Databricks, etc.). Proficiency in programming languages such as Python, R, or Java. Knowledge of cloud AI services (AWS Bedrock, Azure OpenAI, Google Vertex AI). Deploy a Lightweight LLM in a Pharma SaaS Platform Commitment To Diversity & Inclusion: Novartis embraces diversity, equal opportunity, and inclusion. We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards