Biostatistician 2 - Control System Initiative

Division: Siemens Healthineers
Business Unit: Laboratory Diagnostics
Requisition Number: 234136
Primary Location: United States-Massachusetts-East Walpole
Assignment Category: Full-time regular
Experience Level: Mid level
Education Required Level: Bachelor's Degree
Travel Required: 10%
Division Description:
Division Description
Siemens is a global technology powerhouse that has stood for engineering excellence, innovation, quality, reliability and internationality for more than 165 years. As a global technology company, Siemens is rigorously leveraging the advantages that this setup provides. To tap business opportunities in both new and established markets, the Company is organized in nine Divisions: Power and Gas, Wind Power and Renewables, Energy Management, Building Technologies, Mobility, Digital Factory, Process Industries and Drives, Healthineers and Financial Services.
With 45,000 employees Siemens Healthineers is one of the world's largest suppliers of technology to the healthcare industry and a leader in medical imaging, laboratory diagnostics and healthcare IT. All supported by a comprehensive portfolio of clinical consulting, training, and services available across the globe and tailored to customers' needs. So that more people can have a life that is longer, richer, and more filled with happiness.
For more information, please visit: http://www.usa.siemens.com/healthcare
Job Description:
At Siemens Healthineers, we are passionate about enabling healthcare professionals to deliver high quality patient care, and to do so affordably. A leading global healthcare company, Siemens Healthineers continues to strengthen our portfolio of medical imaging and laboratory diagnostics, while adding new offerings such as managed services, consulting, and healthcare IT services - as well as further technologies in the growing market for therapeutic and molecular diagnostics.
Siemens Healthineers develops innovations that support better patient outcomes with greater efficiencies, giving providers the confidence they need to meet the clinical, operational and financial challenges of a changing healthcare landscape.
Control System Initiative - Biostatistician 2
Position Reports To: Director, MFG
The ideal candidate would possess many or all of the following skills:
Advanced understanding of statistical methods and mathematical techniques and how to apply them in a practical way to solve problems
Proven ability to work collaboratively on cross-functional teams representing the statistical discipline
Comfortable assuming ownership of issues and driving to resolution
SAS programming: minimum 3 yrs experience or Advanced Certificate
Working knowledge of Immunoassay technology and techniques
Strong oral and written communication skills
Resiliency and emotional stability under pressure
Complementary skills:
Competence with Microsoft Office tools: Excel, Word, Powerpoint and Outlook
Ability to develop flowcharts and process maps using Visio
Experience working in a regulated environment and familiarity with CFR
Working knowledge of SAS Enterprise Guide, SAS Web Report Studio, and SAS IntrNet
Capable of using SAS Graph and ODS to generate analytical graphics and reports
Ability to utilize SAS Macros to improve efficiency
Understanding of relational database and the ability to develop/modify SQL queries
Familiar with validation and verification activities as applied to SW development
Working knowledge of CLSI and ICH industry guidance documents
Capable of developing statistically sound sampling plans
Capable of preparing clear/concise data summaries and presentations
Capable of providing statistical support for developing Validation and Verification protocols
Capable of developing analytical protocols and rationalizing specifications around performance requirements
Specific Statistical techniques
Confidence Limits
t and f-test
Goodness of Fit
Hypothesis Testing
Non-parametric data analysis
Normality testing and transformations
Odds ratios
Outlier Testing methodologies
Probability and distributions
Randomization functions
Regression techniques
Simulation models
SPC (CpK, Ppk)
Survival Analysis

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