Data Scientist
- Use advanced analytics techniques and build models to answer business questions at the intersection of the pharmaceutical and marketing spaces to provide value to commercial teams
- Dive deep into a variety of data sources to find patterns, explain trends and tie them to business outcomes
- Exhibit deep expertise on statistical/AI/ML techniques combined with strong knowledge of the commercial pharma business and the problems that are being solved by data and analytics
- Effectively work and communicate with global teams and stakeholders to present the final outcomes and provide recommendations as needed.
- Serve as a career advisor/ coach, work with functional leadership and HR to identify career opportunities for team members
- Stay current with respect to ML modelling methodologies, to maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected
- Continuous learning and experimenting new with possibilities for commercial analytics
- Collaborate with cross functional teams and external consultants to help review or translate this work to other team members.
- 8-14 years of in-depth hands-on experience in building models using statistical and ML modelling techniques
- Extensive experience working on the areas of machine learning and artificial intelligence, natural language processing and other approaches to structured/unstructured data, advanced mathematical and predictive modelling, visual analytics etc.
- Demonstrated strength/understanding in statistics (preferred)
- Significant coding experience in R and/or Python
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