Major accountabilities:

• Leading data science projects and effectively communicating results/findings with stakeholders and collaborators. 
• Work collaboratively to develop or leverage cutting-edge AI/ML and Pharmacokinetics/Pharmacodynamics (PK/PD) models for predicting safety and efficacy
• Develop an in-depth understanding of the data and perform data wrangling for use case specific modeling and analytics tasks.
• Actively investigate safety signals leveraging preclinical and clinical data with forward and back translational methodologies to provide actionable insights to support decision-making.
• Independently develop, utilize, and enhance bioinformatics tools and models specifically designed for integrating diverse data types, enabling translational research and analysis.
• Acting as a connector between valuable data resources and project teams, enhancing the generation of hypotheses by sharing insights derived from preclinical and clinical study data.  

Requirements:

• Solid scientific research background, demonstrated ability to ask and answer critical questions using data and AI/ML 
• Effective at communicating and presenting scientific ideas and results to a diverse audience, including peers, stakeholders from different fields, and non-experts 
• Track record of rapidly upskilling in new subject areas to reach a high level of competence. Demonstrated a strong willingness to learn and step out of the comfort zone 
• Education: PhD in a quantitative field such as Computer Science, Physics, Statistics, Data Science, Mathematics or related quantitative field with experience in ML/AI 
• Understanding of disease biology preferred 

Preferred Technical Skills

• Programming & Tools: Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch), R, Spark, Git, Docker, good coding practices (e.g. version control, documentation), High-performance computing (HPC) 
• Data Engineering for analysis/modeling: Data cleaning and preparation, model deployment and optimization, processing big data (e.g. with Spark) 
• Machine Learning & Data Science: Supervised and unsupervised learning (e.g., Gaussian Mixture Models, DBSCAN, Random Forest), Deep learning (e.g. Neutral Networks, Transformers), Feature engineering, Dimensionality reduction (PCA, t-SNE, UMAP), Outlier detection, Statistical methods for inference, prediction and hypothesis testing (e.g. linear and logistic regression), and Data visualization 
• Experience with preclinical and clinical study data. Other related data modalities (e.g. ECG, omics, etc…) would be a plus. 
• Ability to communicate complex analyses and findings to a diverse audience, including effective data visualization.  
• Strong scientific curiosity, initiative, and learning agility. 
• Ability to work as part of an interdisciplinary team, including clinicians, biologists, toxicologists, pathologists, and data scientists.  

Novartis Compensation and Benefit Summary: The pay range for this position at commencement of employment is expected to be between $119,700 and $222,300 per year; however, while salary ranges are effective from 1/1/25 through 12/31/25, fluctuations in the job market may necessitate adjustments to pay ranges during this period. Further, final pay determinations will depend on various factors, including, but not limited to geographical location, experience level, knowledge, skills and abilities. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

You’ll Receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. http://www.novartis.com/careers/benefits-rewards