Job Description Summary

We are seeking a highly motivated, passionate Senior Expert I Data Science to join the data science team of Biologics Research Center (BRC) in San Diego, CA. BRC builds the biologics pipeline in collaboration with Biomedical Research Disease Areas via a breadth of technologies for discovery of antibody, protein, gene therapy and RNA-based therapeutics.

The Senior Expert, Data Science must possess a strong background in Python programming and data analysis skills, have experience working with large-scale datasets using Linux, and demonstrate a thorough understanding of machine learning theory. It is essential to be self-motivated and committed to continuously learning about the latest advancements in the field of data science, given its rapid technological evolution. Curiosity to understand the “why” rather than merely addressing the “how” is crucial for success in this role. The ideal candidate must be an independent researcher, proficient in reviewing existing literature, sourcing solutions online, and devising innovative solutions as required.

Novartis offers a unique environment to apply data science methodologies to large biomedical datasets, enhancing the discovery of new medicines.

Key Responsibilities:

• Collaborate with scientists and bioinformaticians to develop next generation ML/AI models for potency prediction and chemistry optimization using internal and public in vitro and in vivo siRNA datasets.
• Identify, assess, and implement novel algorithms and methodologies from publications to continuously enhance the data science strategy for AI-enabled siRNA design and delivery.
• Effectively collaborate with biologists in data interpretation, visualization, and communication of results
• Contribute to BRC’s AI protein design initiative through AI model evaluation, adoption, integration, and automation.
• Collaborate with other scientists on developing computational solutions to address ad hoc data science challenges.

Essential Requirements: 

• Ph.D. in Data Science, Bioinformatics, Computer Science, or related disciplines
• Experience in machine learning modeling
• Excellent programming skills in Python, with Linux as the operating platform, and familiarity with high-performance clusters. 
• Clear understanding of basic concepts in statistics.
• Accurate understanding of machine learning and deep learning concepts. 
• Previous experience with machine learning applications. 
• Desirable knowledge in deep learning areas, including CNN, GNN, transformers, and language models. 
• Adequate biological knowledge to facilitate effective communication with scientists. 
• Strong communication and interpersonal skills are essential for success in this role. 

Desirable Requirements: 

• Experience with RNAi therapeutics and siRNA design is preferred.

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/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.