Expert Data Science

Job Description Summary

This role involves developing innovative methods for high-visibility projects, bridging academia, technology, and industry partners, and mentoring junior associates. It also requires identifying operational risks, driving issue resolution, and delivering data science-based insights and innovations.

Job Description

Artificial Intelligence and Computational Sciences:  Novartis BioMedical Research

The AI & Computational Sciences (AICS) is the dedicated AI and ML team at Novartis Biomedical Research (BR) innovating across the drug discovery continuum. We aim to accelerate discoveries of transformative medicines for patients worldwide. At AICS, you will take on a hands-on role at the intersection of science, R&D and real-world impact. You will be a part of a truly unique organization with an inter-disciplinary team made up of accomplished scientists who are at the forefront of AI in drug discovery. You will have the opportunity to shape the next wave of drug discovery, combining insights from a wealth of data modalities including diverse omics types like genomics, transcriptomics (including spatial and single-cell), proteomics, compound structures, compound activity, protein structures, measurements from cellular experiments and safety studies, histopathology, clinical imaging, and clinical readouts.

Your Responsibilities:

• Hands-on role developing and implementing innovative methods to deliver on multiple highly visible projects
• Support in building bridges between academia, technology, and industry partners
• Stay up to date in the latest developments of the field while mentoring more junior associates
• Identify and mitigate operational risk while enabling the team to drive issues to resolution across the project
• Design, develop, and deliver various data science-based insights, outcomes, and innovation
• Proactively evaluate the needs of technology and novel scientific software, visualizations, and no approaches to computation to increase efficiently and quality of the Novartis data science practices

What you will bring to the role:

• A deep understanding of Machine Learning and extensive hands-on experience in model building, analysis, and refinement
• Demonstrable experience in topics related to Machine Learning (e.g.: Generative Models, Domain Adaptation, Representation Learning, Image and Vision techniques, NLP and LLM based methods, Biology and/or Chemistry focused approaches, etc.) as they relate to problems and data relevant to life sciences and drug discovery
• Strong skills in Python and relevant Deep Learning frameworks.
• Experience with High Performance Computing systems and Cloud Infrastructures involving large and diverse biomedical data
• Strong communication skills to explain deep technical details, decisions, consequences, and results to non-data science communities
• Deep understanding of datasets and the ability to make data intelligent
• A humble and curious mind that is able to continuously learn while recognizing and applying internal resources to the overall vision and purpose of the team

Key performance indicators:

• Successful implementation based on KPI’s and data management, advanced analytics program objectives  

Minimum Requirements:
Work Experience:

• In-depth mastery of external environment and trends.
• Has a strong professional network across Academia.
• 0-2 years of relevant experience in Data Science.
• Track record delivering global solutions at scale.

Skills:

• Biostatistics, Computer Programming.
• Data Analysis, Data Management. Data Mining.
• Data Quality.
• Data Visualization.
• Databases.
• Deep Learning.
• Graph Algorithms.
• High-Performance Computing.
• Logistic Regression Model.
• Machine Learning (Ml).
• Master Data Management.
• Pandas (Python).
• Python (Programming Language).
• R (Programming Language).
• Random Forest Algorithm.
• Sql (Structured Query Language).
• Statistical Modeling.
• Time Series Analysis.

Languages :

• English.

Skills Desired

Biostatistics, Computer Programming, Data Analysis, Databases, Data Management, Data Mining, Data Quality, Data Visualization, Deep Learning, Graph Algorithms, High-Performance Computing, Logistic Regression Model, Machine Learning (Ml), Master Data Management, Pandas (Python), Python (Programming Language), R (Programming Language), Random Forest Algorithm, Sql (Structured Query Language), Statistical Modeling, Time Series Analysis