Novartis
Healthcare
Sr.SpecialistDDITPO&CFDataScience&AI
“Sr. Specialist DDIT PO&CF Data Science & AI at Novartis. Skills: Data Science, AI, Generative AI, Machine Learning. Contribute to development of AI solutions. Contribute to development of Generative AI solutions”
Industry & Context.
Solve complex business problems
What They're Looking For.
Must Have
7+ years of experience in Data Science & applied ML, Minimum 2-3 years in Gen AI application development, Hands on experience with Python, Hands on experience with ML libraries, Hands on experience with data processing frameworks, Hands on experience with Generative AI tools, Experience applying machine learning algorithms, Experience applying analytical methods, Familiarity with LLMs, Familiarity with prompt design, Familiarity with embeddings, Familiarity with retrieval components, Good understanding of data governance, Good understanding of data quality, Good understanding of data lifecycle fundamentals, Experience with version control, Experience with testing, Experience with basic MLOps workflows, Hands on experience with graph databases, Hands on experience with graph algorithms
Nice to Have
Knowledge of vector databases, Grounding in traditional ML, Grounding in deep learning algorithms, Change management awareness, Stakeholder engagement capability, High learning agility, Curiosity
What You'll Do.
Contribute to development of AI solutions
Contribute to development of Generative AI solutions
Support experimentation
Support feature engineering
Support prompt development
Support model training
Support model evaluation
Implement agentic AI architectures
Implement retrieval workflows
Implement multimodal pipelines
Implement knowledge augmented models
Learn and apply AI tools
Learn and apply agentic AI frameworks
Learn and apply advanced GenAI solution patterns
Support data preparation
Support data enrichment
Support data quality checks
Support alignment with enterprise data lifecycle practices
Develop analytical outputs
Develop model insights
Collaborate with business stakeholders
Understand requirements
Translate requirements into analytical tasks
Translate requirements into model enhancements
Apply core statistical methods
Apply core machine learning methods
Improve performance of deployed models
Improve reliability of deployed models
Implement scalable components
Implement reusable components
Follow MLOps practices
Ensure compliance with Responsible AI principles
Document work clearly
Contribute to shared repositories
Contribute to reusable assets
Contribute to internal best practices
Demonstrate adaptability
Demonstrate continuous upskilling
How You'll Work.
Team & Collaboration
Cross functional teams; Senior data scientists; AI engineers
Communication Scope
Visualization; Storytelling; Clear insights; Concise insights
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