Novartis
From Novartis's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
The AI and Data Science Operations team at BSI Insights supports better decision making at Novartis by using data to generate actionable insights and improve performance. We work with international business units to solve complex problems, develop analytical strategies, apply engineering and machine learning methods, and automate processes for efficiency.
Our team values collaboration and continuous learning, partnering closely with stakeholders across diverse regions to ensure our solutions align with specific business needs. Our work not only drives innovation but also empowers teams throughout Novartis to make informed, impactful decisions based on real-world data.
Build and deliver predictive, classification, machine learning, and statistical models for commercial pharma analytics projects.
Analyze large datasets from sources such as claims, sales, promotions, and other commercial data to generate actionable insights.
Support analytics projects across multi-channel marketing analytics, targeting and segmentation, predictive analytics, resource allocation, optimization, and ad-hoc business requests.
Work closely with senior associates and internal stakeholders to translate business problems into analytical solutions.
Support process improvements, automation, documentation, SOPs, and quality checklists to ensure consistent and high-quality delivery.
Contribute to the exploration and integration of emerging AI technologies, including Generative AI and LLMs.
Manage project delivery with structured communication, documentation, and timely stakeholder updates.
Minimum 2 years of experience in data science, preferably within pharmaceutical, healthcare, life sciences, or analytics domains.
Strong understanding of statistics, predictive analytics, machine learning, and deep learning algorithms.
Hands-on experience in programming languages such as Python, R, or PySpark.
Experience in analyzing large and complex datasets from multiple sources.
Strong problem-solving skills with the ability to develop practical and creative analytical solutions.
Good verbal and written communication skills with the ability to present insights and solutions to stakeholders.
Ability to work independently as an individual contributor and collaborate effectively across teams and time zones.
Desirable Requirements
Experience working with pharma or healthcare datasets such as claims, sales, promotions, targeting, segmentation, or marketing analytics data.
Exposure to commercial pharma analytics, multi-channel marketing analytics, resource allocation, or optimization projects.
Knowledge or hands-on exposure to Generative AI, LLMs, or emerging AI technologies.
Experience in process improvement, automation, SOP creation, quality checks, or project documentation.
Relevant certifications in Data Science, Machine Learning, AI, Python, R, PySpark, Cloud Analytics, or Generative AI would be an added advantage.
Any Full-time Graduate.
Artificial Intelligence (AI), Biostatistics, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Generative AI, Graph Algorithms, Learning Agility, Logistic Regression Models, Machine Learning (ML), Machine Learning Algorithms, Neuro-Linguistic Programming (NLP), Pandas Python Library, Python (Programming Language), R Programming, Statistical Analysis, Structured Query Language (SQL), Time Series Analysis
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