Senior Expert Data Science & AI (Low Molecular Weight Drug Discovery)

Job Description Summary Job Title: Senior Expert Data Science & AI (Low Molecular Weight Drug Discovery) #LI-Hybrid

Location: Hyderabad, India

Relocation Support: Yes

Step into a role where cutting-edge AI meets life-changing science—drive breakthroughs in drug discovery by shaping how intelligent systems design the next generation of therapeutics. As a Senior Expert in Data Science & AI, you will lead the development and application of advanced AI methodologies to accelerate low molecular weight drug discovery, collaborating with world-class scientists to transform complex biomedical challenges into innovative, data-driven solutions that ultimately improve patient outcomes.   Job Description Key Responsibilities Lead technical strategy for artificial intelligence in low molecular weight drug discovery programs. Evaluate emerging model landscapes and identify opportunities for methodological innovation with measurable scientific impact. Design, build, and benchmark algorithms, models, and workflows for hit generation and lead optimization. Translate model performance into decision-ready metrics that improve prioritization, assays, and experimental efficiency. Partner with engineering and product teams to deliver scalable artificial intelligence solutions into research workflows. Collaborate with scientists across medicinal chemistry, structural biology, and disease biology to accelerate design-test-learn cycles. Advance automation by developing agentic workflows for computer-aided drug design pipelines. Guide model robustness and performance with strong validation and close alignment to experimental follow-up. Drive high-value collaborations across Biomedical Research and strengthen artificial intelligence adoption across research teams. Communicate progress, insights, and portfolio impact to leadership to position artificial intelligence as a discovery accelerator.

Essential Requirements 4+ years of experience in machine learning innovation, development, deployment, and model lifecycle management. Proven experience applying machine learning to drug discovery, including generative models and molecular design. Strong proficiency in Python and deep learning frameworks for model development and experimentation. Solid understanding of version control systems such as Git for collaborative software development. Demonstrated expertise in structure-based drug design, including docking, scoring, and pose evaluation. Experience integrating artificial intelligence models with experimental workflows in lab-in-the-loop environments. Ability to design robust, validated models with clear connections to downstream scientific decision-making. Strong collaboration, problem-solving, and communication skills in complex, matrixed environments.

Desirable Requirements Experience working in large global pharmaceutical or biomedical research organizations with complex data ecosystems. Awareness of emerging artificial intelligence methodologies such as foundation models, explainability, and geometric deep learning.

Commitment to Diversity and Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.

Accessibility and accommodation Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to diversityandincl.india@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message

  Skills Desired Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Logistic Regression Model (Inactive), Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai (Inactive), Pandas (Python) (Inactive), Python (Programming Language), R Programming, Stakeholder Engagement, Statistical Analysis, Structured Query Language (SQL), Time Series Analysis