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Location
In office (Hyderabad)
Seniority
Junior · 2+ years exp
Visa
Sponsors visas in Ireland, United States; no register of this country names it
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 13, 2026. Novartis scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Novartis is a Swiss pharmaceutical company created in 1996 by the merger of Ciba-Geigy and Sandoz, two Basel chemical and drug houses with roots in the nineteenth century. It has spent the past decade narrowing itself into a pure innovative medicines business, spinning off its generics arm as Sandoz in 2023 and its eye care business as Alcon in 2019, and now concentrates on cardiovascular, immunology, neuroscience and oncology, including radioligand therapies and gene therapy. Headquartered in Basel and listed in Zurich and New York, it is among the largest research spenders in the industry.

Job Description Summary

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.

Job Description

Key Responsibilities

  • 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.

Essential Requirements

  • 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.

Education

  • Any Full-time Graduate.

Skills Desired

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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