400 This is the number of associates in Global Analytical R&D;, across 4 countries, working tirelessly on cutting-edge and patient centric medicines
YOUR KEY RESPONSIBILITIES:
Your responsibilities include, but are not limited to:
- Translate business questions into analytical problems and build solutions using visualization techniques, machine and deep learning, and statistical modelling
- Develop automated end-user solutions using combined knowledge in data science, modern data systems, and coding
- Search and develop new algorithms, methods, statistical models and business models, providing insight into structured and unstructured data.
- Quickly learns and pilots the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions and to improve status quo
- Provide understandable and actionable business intelligence for key stakeholders.
- Brings understanding of one or more areas of data sciences and is able to demonstrate practical knowledge of techniques
- Helps developing new quantitative methods with the aim of improving processes in various projects and developing new analysis opportunities by integrating existing and new data source
- Support various projects, of limited scope.
- Develop and maintain solutions developed in Microsoft Power Platform
- Develop Deep Learning/Machine Learning-based solutions to assist scientists
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._
Minimum requirements
WHAT YOU’LL BRING TO THE ROLE:
- Education: Bachelors/Masters in Life Science or Information technology
- Mathematical & Statistical Modelling; Algorithm Development; Pattern Recognition & Cognitive Computing; Natural Language Processing; Data Visualizations.
- Knowledge of common data systems, SQL queries, data transformation and report generation; clearly demonstrated proficiency
📌 Data Scientist (Hyderabad)
🏢 Novartis
📍 Hyderabad
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