Job Location: Bangalore/Bengaluru
YOU would be responsible for the following:
As a GSK Global Commercial Data Scientist, you will lead and collaborate with others in GSK in discovery, development, scaling code based statistical modeling, machine learning or artificial intelligence capabilities to be leveraged by global business units and local markets. The primary focus of your efforts will be on streamlining strategic decision information, uncover new opportunities and automating commercial execution to ensure last mile value.
Responsibilities:
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Apply a broad array of analytics skills including machine learning, statistics, text-mining/NLP, and modeling to extract insights from structured and unstructured data sources and complementary real-world digital information streams to business challenges
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Developing and evolving core commercial models used across all analytics packages. Examples of the models will be: Multi-Channel Analytics, Patient Pathways, Referral Networks, Patient Adherence Metrics, Omni-Channel Segmentation and Patient Funnels
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Develop modularized data with patient-centric metrics for integration with Dashboards, Reporting or predictive modeling.
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Design data test and learn experiments to drive personalized solutions across the customer journeys addressing key customer needs as well as enabling personalized experiences across each touch points through connective analytics.
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Collaborate across business to prototype, launch and Iterate analytics capabilities that quickly scale globally
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Lead the collaborate with local and global teams to ensure data driven decisions are embedded into business process.
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Automate analytics models and simplify information management
Qualifications:
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2+ years of professional experience in advanced analytics, full-time employment in mid-large organizations with focus on Marketing and Customer Analytics, ideally with U.S. Pharma anonymized patient longitudinal data
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Bachelor s degree in Economics, Statistics or Operations Research.
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Desirable to have certifications in Data Science tools and methodologies.
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Strong written and verbal communication skills
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Excellent problem solving and data analysis skills, with hands-on experience in relevant analytical approaches and models, including non-supervised models such as Decision Trees and Cluster analyses.
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Develop insights and storylines through translation of analysis and modeling
We are looking for professionals with these skills to achieve our goals. If YOU have these skills, we would like to speak to you.
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Hands on experience using Apache Spark, Python, R, SQL and Data Visualization tools
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Experience in using anonymized patient level longitudinal data to characterize treatments using fields such as diagnosis codes, procedure codes and demographic attributes.
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Knowledge of the data landscape in healthcare (EHR, claims data, real world data, HEOR data)
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