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Associate Director, Data Scientist
Johnson & Johnson
Horsham, PA, United States
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The Methods & Analysis group is part of the Global Medical Safety organization in Johnson & Johnson. The group consists of several highly creative and forward-thinking scientists and programmers focused on bringing quantitative rigor and solutions to the field of medical safety. Currently, the group is expanding its scope to include novel Machine Learning and AI technologies to complement their skillsets in biostatistics and mathematical modeling. The group collaborates extensively with physicians, health care professionals, and other scientists in Global Medical Safety, J&J Consumer sector, and external colleagues in the pharma industry and academia. We are currently seeking an Associate Director, Data Science to be located in Horsham, PA or Titusville, NJ
The Associate Director, Data Scientist will conceive, develop and implement end to end data science solutions. The scientist will be part of a dynamic, accomplished team that supports multiple sectors.
• Identify, extract, clean, de-duplicate and prepare data sets for safety physicians and teams
• Develop and implement machine learning models for decision making in support of drug safety processes (eg triage)
• Apply Machine Learning techniques to safety signal detection
• Apply Big Data techniques to textual information in support of signal management
• Develop and provide integrated visualizations of all data sources
• Develop and apply creative solutions that go beyond current tools to deliver data-driven insights to high-priority scientific problems in GMO
• Participate in project teams and interact closely with scientific colleagues across various disciplines
• Ensure seamless collaborations and alignment in the Data Analytics CoE and other GMO functions in order to contribute to the delivery of projects with high levels of quantitative scientific expertise, operational excellence and quality;
• Promote innovation and collaboration in GMO;
• Provide tailored training on Data Sciences to members of the Data Analytics CoE and, as needed, other GMO functions.
• Collaborate with other functions to leverage development opportunities for staff;
Qualifications
• Master’s degree in Computer Science, Statistics, Machine Learning & Artificial Intelligence, Physics, Mathematics, Computational Chemistry, Bioinformatics, Computational Biology or a related discipline is required.
• Strong working knowledge of machine learning algorithms such as Neural Networks, Random Forest, SVM, etc.is required
• Working knowledge of Natural Language Processing techniques is required.
• A minimum of 3 years of industry experience in Data Sciences is preferred.
• Pharmaceutical industry experience is preferred.
• Familiarity with clinical development and drug safety is preferred. Handling of healthcare relevant datasets, such as EHR, insurance claims or registry data, is preferred.
• Experience in cleaning /correcting/de-duplicating large datasets
• Familiarity with large datasets, understanding of data analysis workflows, and/or knowledge of querying languages such as SQL is required.
• Proficiency with one or more programming languages such as Python and/or R, is required.
• In-depth knowledge of standard analytical software, e.g., SAS/JMP, SAS, or R is preferred.
• Experience with visualization software/tools, specifically Qlik and/or Spotfire, is preferred.
• A working knowledge of applied epidemiologic and public health principles is preferred.