Job Description Summary
Location: London, UK; Dublin, IrelandJob Description
Key Responsibilities:
Develops AI & automation tools & solutions to accelerate work with clinical documents and data.
Drives development of IT infrastructure to enable Quantitative Sciences to utilize novel methods for automation and AI – work with vendors and Novartis IT to deploy solutions in the Novartis IT ecosystem.
Provides technical leadership for applied AI and automation projects
Builds strong collaborative working relationships and communicates effectively with Quantitative Science partners along with clinical teams to promote a greater mindset where associates may leverage new technology safely in an open and transparent manner.
Plays a lead role in applying AI & automation through consulting, providing guidance on for complex data and unplanned data challenges.
Propose and implement improvements to existing processes, form a Risk, Quality & Compliance, and ensure compliance with legal and regulatory requirements, as well as data security and privacy best practices.
Ensure all AI & automation solutions are well-documented.
Identify and mitigate risks related to AI & automation tools and projects.
Stays updated with industry trends and advancements, and helps establish and strengthen the link between Novartis and the external AI community through open-source contributions and publications, as well as through external congresses, conferences, and other scientific workshops and meetings.
Encourage a culture of continuous learning, constructive collaboration, and innovation within the team, and delegate and collaborate on tasks and projects to ensure the team meets deadlines.
What you will bring to the role:
MSc or PhD in Computer Science/Engineering, Data Sciences, Bioinformatics, Biostatistics or any other computational quantitative science
Minimum of 3-6 years of developing technical solutions for automation or AI.
Expert in software / AI engineering practices (including versioning, release management, deployment of models, agile & related software tools).
Strong software development skills in R and Python, deep learning & analytical frameworks such as pytorch, jax, tensorflow.
Ideally prior experience in life sciences or drug development.
Expertise in systems programming languages (e.g. C/C++/Rust).
Strong working knowledge of at least one large-scale data processing technology (e.g. High-performance computing, distributed computing), databases and underlying technology (cloud or on-prem environments, containerization, distributed storage & databases…)
Strong interpersonal and communication skills (verbal and written) effectively bridging scientific and business needs; experience working in a matrix environment
Proven record of delivering high-quality results in quantitative sciences and/or a strong scientific publication track record
Experience in Artificial Intelligence (Ai), Big Data, Data Governance, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Master Data Management.
Experience in Machine Learning (Ml), Python and R, Statistical Analysis.
Benefits and rewards:
Read our handbook to learn about all the ways we’ll help you thrive personally and professionally:
https://www.novartis.com/careers/benefits-rewards
Commitment to Diversity & Inclusion:
We are 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 all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in any order to receive more detailed information about essential functions of a position, please send an e-mail to inclusion.switzerland@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
Apache Spark, Artificial Intelligence (AI), Big Data, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Machine Learning (Ml), Master Data Management, Python (Programming Language), R (Programming Language), Statistical Analysis