Novartis
Hyderābād
Position Purpose:
Understands business problems, supports integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. Provide data science and quantitative analytical support by ensuring timely delivery of high-quality reports. Build capabilities to leverage the Science of data.
Your Key Responsibilities:
Your responsibilities include, but not limited to:
- Under guidance of their supervisors and team members and gradually more independently -Translate business questions into analytical problems and build solutions using visualization techniques, machine and deep learning, and statistical modeling
- 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 wide range of critical business questions and to improve status quo -Identifies research articles and reproduce /apply innovative methodology to Novartis business problems
- 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 sources -Support various projects, of limited scope.
- Reporting of technical complaints / adverse events / special case scenarios related to Novartis products within 24 hours of receipt and Distribution of marketing samples (where applicable)
What you’ll bring to the role:
- English Knowledge of data-sources and has a strong professional network across Academia.
- In-depth mastery of external environment and trends, Track record delivering global solutions at scale Information & Decision Theories, Data Visualization, Machine Learning & Deep Learning, Big Data, Applied Mathematics, Predictive Modelling and Data Management
- 3+ years of relevant experience in Data Science Natural Language Processing Data Science Libraries Data Mining Python, R.
- Masters in Statistics, Operational Research, Computer Science or in a quantitative field from top University.
Why Novartis?
769 million lives were touched by Novartis medicines in 2020, and while we’re proud of this, we know there is so much more we could do to help improve and extend people’s lives.
We believe new insights, perspectives and ground-breaking solutions can be found at the intersection of medical science and digital innovation. That a diverse, equitable and inclusive environment inspires new ways of working.
We believe our potential can thrive and grow in an Unbossed culture underpinned by integrity, curiosity and flexibility. And we can reinvent what’s possible, when we collaborate with courage to aggressively and ambitiously tackle the world’s toughest medical challenges. Because the greatest risk in life, is the risk of never trying!
Imagine what you could do here at Novartis!
Commitment to Diversity & Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse team’s representative of the patients and communities we serve.
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network
Commitment to Diversity & Inclusion:
Minimum requirements
- 3+ years of relevant experience in Data Science Natural Language Processing Data Science Libraries Data Mining Python, R.
- Masters in Statistics, Operational Research, Computer Science or in a quantitative field from top University
Division
Business Unit
Country
Work Location
Company/Legal Entity
Functional Area
Job Type
Employment Type
Shift Work
Early Talent
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