Real-World Evidence Data Scientist

Role Overview: As a Real-World Evidence Data Scientist at Sanofi Business Operations, your main responsibility will be to provide a high level of expertise in employing cutting-edge analytical & computational approaches to drive evidence-based pharmaceutical product development. You will be expected to offer scientific and technical leadership in machine learning and AI, collaborating closely with various disciplines across Sanofi to deliver cutting edge analysis to key business questions. Key Responsibilities: - Utilize Machine/Deep Learning techniques to elucidate disease trajectories, patient subtypes, define underdiagnosed conditions, and identify unmet health needs. - Create a framework for generating re-usable models and insights across big-data (e.g. EHRs, claims) and rich small data sets (e.g. clinical trials, imaging). - Generate insights by merging diverse data streams such as health, surveillance, trend data, sensor, and imaging. - Adopt emerging technology into an analytical framework, including distributed analytics and graph databases. - Act as a subject matter expert in machine learning, statistical and/or modeling on team projects. - Work with internal and external study leads to execute Advanced Analytics projects and studies. - Implement and execute computational and statistical methodologies in Advanced Analytics for RWE. - Provide expertise and execute advanced analytics for solving problems across R&D, Medical Affairs, HEVA, and Market Access Strategies and Plans. - Apply a broad array of capabilities spanning machine learning, statistics, mathematics, modeling, simulation, text-mining/NLP, and data-mining to extract insights and communicate efforts across the company. - Plan and deploy methodological standards, standardized processes, demos, and POCs for the companys highest priority business needs. - Contribute to the design, development, and implementation of Sanofis data science architecture and ecosystem to guide decision-making and build foundational capabilities. Qualifications Required: - PhD in quantitative field such as Statistics, Biostatistics, Applied Mathematics, or related field with 6 years of industry or academic experience; or Relevant Masters Degree with 10 years of related industry or academic experience. - Strong oral and written communication skills. - Ability to work and collaborate effectively in a team environment. - Excellent knowledge of the English language (spoken and written). [Additional Details: Omit as no additional details of the company are provided in the job description.] Experience Level: Senior Level Role Overview: As a Real-World Evidence Data Scientist at Sanofi Business Operations, your main responsibility will be to provide a high level of expertise in employing cutting-edge analytical & computational approaches to drive evidence-based pharmaceutical product development. You will be expected to offer scientific and technical leadership in machine learning and AI, collaborating closely with various disciplines across Sanofi to deliver cutting edge analysis to key business questions. Key Responsibilities: - Utilize Machine/Deep Learning techniques to elucidate disease trajectories, patient subtypes, define underdiagnosed conditions, and identify unmet health needs. - Create a framework for generating re-usable models and insights across big-data (e.g. EHRs, claims) and rich small data sets (e.g. clinical trials, imaging). - Generate insights by merging diverse data streams such as health, surveillance, trend data, sensor, and imaging. - Adopt emerging technology into an analytical framework, including distributed analytics and graph databases. - Act as a subject matter expert in machine learning, statistical and/or modeling on team projects. - Work with internal and external study leads to execute Advanced Analytics projects and studies. - Implement and execute computational and statistical methodologies in Advanced Analytics for RWE. - Provide expertise and execute advanced analytics for solving problems across R&D, Medical Affairs, HEVA, and Market Access Strategies and Plans. - Apply a broad array of capabilities spanning machine learning, statistics, mathematics, modeling, simulation, text-mining/NLP, and data-mining to extract insights and communicate efforts across the company. - Plan and deploy methodological standards, standardized processes, demos, and POCs for the companys highest priority business needs. - Contribute to the design, development, and implementation of Sanofis data science architecture and ecosystem to guide decision-making and build foundational capabilities. Qualifications Required: - PhD in quantitative field such as Statistics, Biostatistics, Applied Mathematics, or related field with 6 years of industry or academic experience; or Relevant Masters Degree with 10 years of related industry or academic experience. - Strong oral and written communication skills. - Ability to work and collaborate effectively in