The Role
Lead design and delivery of scalable data pipelines, ML models, and analytical workflows to support PK, ADME, and PK/PD-driven drug discovery. Partner with wet and dry lab teams, deploy production-grade data products, apply statistical and ML methods to large experimental datasets, and communicate findings to drive decision-making and automation.
Summary Generated by Built In
Job Description Summary
Join the Modeling & Simulation Data Science team within the Translational Medicine, Pharmacokinetic Sciences Unit to advance data-driven drug discovery. This role combines advanced data science with robust software engineering to transform large-scale experimental datasets into impactful insights and scalable digital solutions supporting drug discovery and development.We are seeking for a talent to provide support at Biomedical Research India within Pharmacokinetic Sciences (PKS) Modeling & Simulation, focusing on lead identification and optimization in close collaboration with Novartis colleagues in the US and Switzerland, to discover and advance innovative methods addressing areas of high unmet medical need. The PKS department handles a high volume of experimental data across ADME, PK and PD domains. This role plays a critical part in leveraging these data through advanced analytics, machine learning, and software engineering to inform decision-making, accelerate lead optimization, and enhance reproducibility and scalability of scientific workflows.
Job Description
Major accountabilities:
- Serve as a trusted partner between Data & Digital (D&D) and PKS wet and dry lab teams to identify gaps and translate business needs into strategically aligned solutions within the D&D portfolio.
- Act as a data science representative in Integrated Drug Discovery (IDD) programs, providing scientific and strategic input using experimental and computational data.
- Design, build, and maintain scalable data pipelines, applications, and analytical workflows.
- Develop, deploy, and maintain machine learning models to uncover structure–property relationships and support decision-making.
- Apply statistical analysis and data mining techniques to derive insights from complex biological and chemical datasets.
- Write production-quality, maintainable code following software engineering best practices (testing, version control, documentation).
- Collaborate across cross-functional teams to integrate computational solutions into scientific workflows.
- Identify opportunities for automation, improved data usage, and development of in silico models and digital tools.
- Communicate findings clearly to diverse audiences and contribute to the adoption of data-driven approaches.
Minimum requirement
- PhD in life sciences, computational biology, cheminformatics, bioinformatics, or a related field, and 3-4 years (PhD) / 7-8 overall years of relevant work experience in drug discovery within biomedical or pharmaceutical research settings.
- Strong expertise in machine learning, statistics, and data science workflows applied to drug discovery.
- Proficiency in Python and/or R with solid software engineering practices.
- Experience designing and deploying production-grade data products or ML systems.
- Strong understanding of data visualization and exploratory analysis.
- Excellent communication skills and ability to translate complex concepts into actionable insights.
- Experience in pharmacokinetics (PK), ADME, or PK/PD modeling.
- Familiarity with modern application frameworks or front-end technologies (e.g., JavaScript, Svelte).
- Experience with advanced ML methods such as deep learning or generative models.
- Experience working with large-scale scientific datasets and data platforms.
Skills Desired
Artificial Intelligence (AI), Biostatistics, Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series AnalysisSkills Required
- PhD in life sciences, computational biology, cheminformatics, bioinformatics, or related field and 3-4 years (PhD) / 7-8 overall years of relevant drug discovery experience
- Strong expertise in machine learning, statistics, and data science workflows applied to drug discovery
- Proficiency in Python and/or R with solid software engineering practices (testing, version control, documentation)
- Experience designing, deploying, and maintaining production-grade data products or ML systems
- Experience with pharmacokinetics (PK), ADME, or PK/PD modeling
- Experience working with large-scale scientific datasets and data platforms
- Strong understanding of data visualization and exploratory analysis
- Excellent communication skills and ability to translate complex concepts into actionable insights
- Familiarity with modern application frameworks or front-end technologies (e.g., JavaScript, Svelte)
- Experience with advanced ML methods such as deep learning or generative models
- Artificial Intelligence (AI) experience
- Biostatistics experience
- Business value creation experience
- Change management experience
- Data governance experience
- Data literacy and data quality practices
- Graph algorithms experience
- Stakeholder engagement experience
- Time series analysis experience
- Curious mindset and learning agility
Novartis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Novartis and has not been reviewed or approved by Novartis.
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Healthcare Strength — Pay and benefits are described as a strong overall package, supported by medical, dental, and vision insurance alongside FSAs/HSAs and disability and life coverage. Mental-health support is reinforced through an employee assistance program with psychological support and a network of mental health first aiders.
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Retirement Support — Retirement support is positioned as a standout element, with an automatic company contribution plus dollar-for-dollar matching in the 401(k). Additional retirement funding is described through an age-based defined contribution program and access to an employee share purchase plan discount.
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Parental & Family Support — Family-related benefits are framed as robust, including a global minimum of paid parental leave for new parents following birth or adoption. Added supports include domestic partner coverage, dependent-care resources, and benefits such as adoption assistance and child/elder care options.
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The Company
What We Do
Novartis is an innovative medicines company. Every day, working to reimagine medicine to improve and extend people’s lives so that patients, healthcare professionals and societies are empowered in the face of serious disease. Our medicines reach more than 250 million people worldwide.
