Skill: biostatistics , clinical study , data management , data interpretation , research , clinical , personal care , statistical analysis; Exp: 0-3 years; Asst R&D Manager ( Job Number 18000FAR ) Location India-Karnataka-Bangalore-Unilever R&D Bangalore Job Field Research/Development Posting Date Oct-19-2018 End Date Dec-01-2018 Job Type Regular Shift Day Job Job Schedule Full-time Description No matter who you are, or where in the world you are, the chances are that our products are a familiar part of your daily routine. Every day, around the world, people reach for Unilever products. Our brands are trusted everywhere and, by listening to the people who buy them, we’ve grown into one of the world’s most successful consumer goods companies. In fact, 150 million times a day, someone somewhere chooses a Unilever product. Look in your fridge, or on the bathroom shelf, and youre bound to see one of our well-known brands. We create, market and distribute the products that people choose to feed their families and keep themselves and their homes clean and fresh. Job Title Asst. R & D Manager, Clinicals – Biostatistics Location Bangalore Clinicals is part of the Beauty & Personal Care Division within Unilever R&D and supports clinical studies across Skin, Hair, Deo and Oral Care. The Biostatistics team is responsible for ensuring that these studies are designed and analysed in a defensible way, so that results can be used to both support claims and provide scientific insights. Requirements & Qualifications The candidate should ideally have at least a Masters Degree in Statistics, with at least three years experience in research or the FMCG/Pharmaceutical industries, although applications from less experienced candidates will be considered. He/she should have strong written and oral communication skills. Experience in the following areas is required Applied statistics in scientific research, actionable insights and problem solving. Hands-on technical expertise in data management, visualization, and a range of statistical analysis techniques including methods for randomization and linear modelling. Extensive knowledge of statistical software including SAS. Experience in collaborating effectively in global teams across time-zones, cultures and organizational boundaries. Excellent communication and influencing skills. Responsibilities Engagement and collaboration with globally deployed, multi-disciplinary teams to design and implement efficient, well-focused, statistically fit-for-purpose studies, analyze, visualize and interpret data. Work in inter-disciplinary teams that includes clinical study experts, measurement scientists, bioinformaticians, and other statisticians, both within Unilever and with external partners. Provision of statistics expertise across a range of R&D disciplines to define and implement statistical solutions. Responsibility for the quality and defensibility of study designs, statistical analyses, models and data interpretation.
Function: Biotech / Pharma / R&D