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Position: (Senior) Biostatistician (F/M)
Institution: Royal DSM
Department: Nutritional Products division
Location: Kaiseraugst, near Basel, Switzerland
Duties: You will support our multidisciplinary project teams with your statistical expertise to optimize decisionmaking and influence strategy in all development phases of our nutritional products, from early research through development and marketing: Provide data analysis, meta-analysis, visualization, reporting and interpretation for a wide variety of research questions in nutrition and health; Optimize the design and statistical power of feeding studies in farm animals and of clinical studies in humans
Requirements: MSc in (Bio-)Statistics or a related field, PhD preferred; At least 3 years of practical experience in applying statistics in a life science environment (PhD in relevant field considered as 3 years); Sound knowledge of standard statistical methods, particularly regression and extensions (GLMM). Experience with high-dimensional data is an asset. You are an experienced R user. Basic programming competence in Python, Stata or other languages is an advantage
   
Text: DSM - Bright Science. Brighter Living.™ Royal DSM is a global science-based company active in health, nutrition and materials. By connecting its unique competences in life sciences and materials sciences DSM is driving economic prosperity, environmental progress and social advances to create sustainable value for all stakeholders simultaneously. DSM and its associated companies deliver annual net sales of about €10 billion with approximately 25,000 employees. The company is listed on Euronext Amsterdam. Our nutrition division is the global leader in ingredients for feed, food, personal care and pharmaceuticals and accounts for about 70% of DSM group EBITDA. It is realizing its ambitious growth targets in a complex, ever-changing and increasingly competitive environment. The Challenge Are you excited about scientific innovation and would like to provide statistical advice and insights to our research and development community? Then our position as Biostatistician / Senior Biostatistician (f/m) might be the right next step for you! We are looking for a bright, motivated colleague to further strengthen our statistical consulting and data analysis team in the Innovation Center of our Nutritional Products division in Kaiseraugst, near Basel. The position You will support our multidisciplinary project teams with your statistical expertise to optimize decisionmaking and influence strategy in all development phases of our nutritional products, from early research through development and marketing:  Provide data analysis, meta-analysis, visualization, reporting and interpretation for a wide variety of research questions in nutrition and health  Optimize the design and statistical power of feeding studies in farm animals and of clinical studies in humans  Monitor outsourcing of statistical analyses to partner organizations and ensure compliance with official statistical guidelines  Work closely and in a result-oriented way with study directors, project managers, nutritionists, data managers, external study sites, regulatory affairs, marketing and customers, either as a project team member or as an ad-hoc consultant  Participate in our digital transformation strategy and optimize how we organize and leverage data  Participate in collaborations on a global basis (research institutions, customers, CROs, NGOs, etc.) Location and Conditions  Location: Kaiseraugst, Switzerland  Conditions: Permanent, full-time (100%) Procedure & contact Interested in this position? Please apply on-line by uploading your CV and motivation letter in English at www.dsm.com/careers. For additional questions, please contact Evelien Vlap, Talent Acquisition Business Partner at evelien.vlap@dsm.com or Dr. Franz Roos, Competence Lead Biostatistics at franz.roos@dsm.com, +41 61 815 82 09. Reference check procedures are part of the DSM Recruitment and Selection Process. You will be contacted when these references checks are required. The ideal profile  MSc in (Bio-) Statistics or a related field, PhD preferred  At least 3 years of practical experience in applying statistics in a life science environment (PhD in relevant field considered as 3 years); extra experience is an asset  Sound knowledge of standard statistical methods, particularly regression and extensions (GLMM). Experience with high-dimensional data is an asset.  You are an experienced R user.  Basic programming competence in Python, Stata or other languages is an advantage  As an all-rounder, you enjoy the variety of projects, people and questions that are typical for this role.  You are used to handling several projects at once with a proven ability to prioritize and to meet deadlines.  You enjoy being the point of contact for your stakeholders. You are curious about the goals and the context of projects and you proactively contribute to their success  You are a strong team-player with the ability to communicate effectively with non-statisticians and who thrives in an open and collaborative research environment, but you are independent as well  Any professional or extracurricular activities where you refined your team work, leadership and organizational skills are considered as assets  Experience with biology, life science, clinical studies, data management, relational databases or CDISC standards is an advantage  Fluent in English. German would be an asset. The Reward Working for DSM means the opportunity to really contribute to improve people’s lives and solving the challenges of today’s world. Challenging jobs, career opportunities and an inspiring environment allow you to enhance your personal development. DSM recognizes that the on-going success of the company depends on the continued development and engagement of our employees and pursues a fair and competitive remuneration policy, recognizing individual and team competencies and performance. Royal DSM is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, status as a qualified individual with a disabil
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