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The Head of Biopharma Biostatistics serves as a leader within the global biostatistics department responsible for strategic and operational oversight of the biostatistics and statistical programming activities for Emmes' biopharma portfolio in key therapeutic areas such as vaccine and infectious diseases, ophthalmology, CNS, rare disease and cell and gene therapy among others.
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This position will work closely with the Vice President of Biostatistics and Executive Director of Data Management and Statistical Programming and other members of the clinical, pharmacovigilance and regulatory affairs teams to provide programming support across all programs.
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Proficiency in statistical methods (eg, linear regression, logistic regression, survival analysis, ARIMA), AI/machine learning techniques (eg, Random Forest, XGboost, Clustering, Neural Network, NLP, Image Recognition) and programming languages (eg, Python, R, SAS, SQL.
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A Bachelor's degree from an accredited four-year college or university in social work, psychology, sociology, public health, health education, planning, public administration, community health, urban planning, policy analysis, quantitive or statistical analysis or closely related field and three (3) years of experience with professional responsibility for planning or administrative functions such as coordinating or planning community programming for specific populations.
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Statistical Programming Management: Coordinates outsourced statistical programming of analysis data sets and tables, listings, and figures (TLFs) needed for clinical study reports and regulatory submissions, as well as in-house validation of this work.
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Lead the statistical programming activities for regulatory submissions following CDISC standards. Hands-on statistical programming for CSR, publications, presentations, DSUR, IB, safety data review, and ad hoc analyses.
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Located at the Redstone Arsenal in Huntsville, AL. In your role as a Data Scientist, you will use statistical techniques to plan tests and analyze and interpret data. ERC is a premier provider of customer-driven, cost-effective, and quality Engineering Services; Enterprise Systems and Applications; Human Factors Engineering; Information Technology and Cyber Security; Professional Services; and Specialized Engineering Solutions to the Department of Defense, Federal Aviation Administration, Nuclear Regulatory Commission, and other Federal Agencies.
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You will provide programming support to statisticians in production of summary tables, data listings and graphs required for clinical trials, and CDISC datasets for regulatory submission.
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Collaborates with RWE Platforms and Partnerships colleagues, EvGen Strategic Planning Innovation, Biostatistics, Statistical Programming and Digital to identify and fill RWD gaps using fit-for-purpose sources worldwide, incorporate advanced analytical and machine learning approaches, and scale innovations across category teams.
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Outside of the Platform, the Head will work with leaders from Biostatistics & Data Management, Global Regulatory Affairs, Clinical Pharmacology / Pharmacometrics, HEOR, Legal/Compliance, and others to achieve research and business objectives.
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The Sr. Statistical Programmer will create specifications and develop SAS programs for data tabulation, analysis and reporting that comply with regulatory requirements (CDISC SDTM and ADaM), SOPs/ SAP, and lead junior level programming personnel.
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They will also serve as a trusted expert with study / analytical KOLs, key regulatory agencies (e.g., FDA in the US, EMA in Europe, MHRA in the UK, PDMA in Japan, CDE in China), HTAs/Payers, and other stakeholders.
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Managers of Statistical programming provide comprehensive programming expertise to clinical project teams to support the development, regulatory approval and market acceptance of Bristol Myers Squibb (BMS) products.
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10+ years of relevant experience in Financial Services, especially in the areas associated with Risk and Control, Internal Audit, AML transaction monitoring, Sanctions, Compliance and Regulatory Risk.
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Independently provides strategic statistical input to drug development planning, including feasibility assessments, development plans, complex/innovative study designs, novel statistical methodology, interpretations, regulatory submissions (NDA, MAA and JNDA) and follow up.
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